diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..fae342f3a189b4f08e4afa46d8eee21adc786a41 --- /dev/null +++ b/.gitignore @@ -0,0 +1,51 @@ +# macOS +.DS_Store +._* +.AppleDouble +.LSOverride +.Spotlight-V100 +.Trashes +.fseventsd + +# Windows +Thumbs.db +ehthumbs.db +Desktop.ini + +# Linux +*~ +.directory + +# Python +__pycache__/ +*.py[cod] +*$py.class +*.so +.Python +*.egg-info/ +.pytest_cache/ +.mypy_cache/ +.ruff_cache/ +.ipynb_checkpoints/ + +# Editors / IDEs +.idea/ +.vscode/ +*.swp +*.swo +*.bak +*.tmp + +# Local virtual envs (should never be committed to a dataset repo) +.venv/ +venv/ +env/ + +# Hugging Face / huggingface_hub local cache (in case it gets created here) +.cache/ +.huggingface/ + +# Logs / scratch +*.log +scratch/ +tmp/ diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ea11f45247175429370d3340b3d54d6577917698 --- /dev/null +++ b/README.md @@ -0,0 +1,278 @@ +--- +pretty_name: PowerZoo Dataset +license: other +license_name: mixed-upstream-licences +language: + - en +size_categories: + - 1M *****.** Author names, affiliations and contact information are intentionally omitted during the review period, in compliance with ***. + +--- + +## 1. Why this dataset? + +Power-system RL benchmarks have historically suffered from three gaps: + +1. **Synthetic load curves** that do not capture the multi-scale structure of real demand (sub-hour ramping, weekly seasonality, event-driven spikes). +2. **Inconsistent grid topologies** scattered across `MATPOWER`, `pandapower`, OpenDSS, IEEE PES test feeders, etc., each with its own conventions. +3. **No canonical link** between high-fidelity demand traces and a fixed set of grid topologies, making cross-paper comparison difficult. + +PowerZoo Dataset addresses all three by shipping (a) cleaned, parquet-encoded traces from public regulators and cloud providers under a single schema, (b) a unified Python representation of standard transmission and distribution test cases, and (c) lightweight JSON manifests that wire the two together for reproducible experiment configuration. + +--- + +## 2. Repository layout + +``` +PowerZooDataset/ +├── README.md # this file +├── parquet/ # harmonised time-series traces +│ ├── *.parquet # primary data files +│ └── *.json # per-file provenance metadata (rows, dtypes, source URL, generation timestamp) +├── manifests/ # loader manifests (column maps, derivations, normalisation) +│ └── .json +└── powergrid_case/ # electrical-network case definitions (Python) + ├── CaseBase.py # ClearCase base class + ext. DataFrame + ├── transmission/ # HV / sub-transmission test systems + │ ├── Case5.py, Case14.py, Case29GB.py, Case118.py, + │ ├── Case300.py, Case552GB.py, Case1354pegase.py, Case2383wp.py + │ └── __init__.py + └── distribution/ # MV distribution test feeders + ├── Case33bw.py, Case118zh.py, Case123.py, Case141.py, + ├── Case533mt_hi.py, Case533mt_lo.py + └── __init__.py +``` + +### 2.1 Parquet traces + + +| File | Domain | Resolution | Rows | Columns | Bytes | +| ---------------------------------------------------- | --------------------------------------------- | ---------- | --------- | ------- | ------- | +| `AEMO_5min_Demand_2025_2026.parquet` | AU NEM demand (5 regions) | 5 min | 737,400 | 5 | 6.5 MB | +| `AEMO_Forecast_vs_Actual_2025.parquet` | AU NEM probabilistic forecast vs. actual | 30 min | 89,145 | 10 | 1.6 MB | +| `Ausgrid_Zone_Substation_FY25_imputed_15min.parquet` | NSW zone substations (175 sites) | 15 min | 6,095,040 | 4 | 60 MB | +| `GB_NESO_Demand_2009_2025_30min.parquet` | GB NESO historical demand | 30 min | 285,454 | 22 | 4.7 MB | +| `GB_Forecast_Actual_Demand_2023_2025_30min.parquet` | GB day-ahead forecast vs. actual | 30 min | 48,283 | 3 | 0.8 MB | +| `GB_Gen_by_Type_2016_2025_30min.parquet` | GB generation by fuel type | 30 min | 180,048 | 13 | 6.2 MB | +| `MID_GB_30min_aligned_to_gen.parquet` | GB APX/N2EX mid prices & volumes | 30 min | 48,283 | 6 | 0.8 MB | +| `alibaba_dc_2018_300s.parquet` | Alibaba production cluster (CPU/mem/net/disk) | 5 min | 2,243 | 6 | 0.1 MB | +| `alibaba_gpu_2020_300s.parquet` | Alibaba GPU cluster (GPU/CPU util) | 5 min | 415 | 3 | <0.1 MB | +| `azure_dc_v2_300s.parquet` | Azure VM trace v2 (CPU, assigned memory) | 5 min | 8,640 | 3 | 0.2 MB | +| `google_dc_2019_300s.parquet` | Google Borg 2019 (CPU/mem/CPI) | 5 min | 8,064 | 5 | 0.3 MB | + + +Each `*.parquet` ships with a sibling `*.json` capturing source URL, source organisation, generation timestamp, exact column dtypes, region/category enumerations and (where applicable) timezone conventions. + +### 2.2 Manifests + +Manifests in `manifests/` are the contract used by PowerZoo / PowerZooJax loaders. A manifest declares: + +- `parquet_file` and the matching `metadata_json` +- `column_map`: rename rules from raw column → canonical schema (e.g. `OPERATIONAL_DEMAND → load.actual_mw`) +- `index_map`: which raw columns serve as `datetime` / `region` / `issue_time` / `target_time` +- `derived`: closed-form derivations from raw columns (e.g. `wind.available_mw = "Wind Offshore + Wind Onshore"`) +- `normalize`: per-channel scaling factors applied at load time +- `time_mode`: `calendar` (absolute UTC) or `profile` (cyclical, anchored to `data_epoch`) +- `region_values`, `date_range`, `source_url`, `source_organization` + +The 11 manifests cover every parquet file shipped here. Note that `gb_neso_demand` uses a two-column index (`SETTLEMENT_DATE` + `SETTLEMENT_PERIOD` 1–50) instead of a single `datetime` column — the manifest's `datetime_recipe` field documents the exact reconstruction (Europe/London tz-localise then convert to UTC; SP=49–50 absorb the autumn clock-change repeat). + +### 2.3 Power-grid case files + +`powergrid_case/` contains a unified Python representation for both transmission and distribution test systems. Every case subclasses `ClearCase` and exposes four `pandas.DataFrame` tables in MATPOWER-compatible units (MW, MVAr, p.u.): + +- `nodes` — `id, type (1=PQ / 2=PV / 3=Ref), Pd, Qd, x, y` +- `units` — `id, bus_id, mc_a, mc_b, mc_c, p_max, p_min` (quadratic cost + capacity) +- `lines` — `id, from, to, x, floor, cap` (reactance + thermal limits) +- `loads` — `id, bus_id, mc_a, mc_b, mc_c, d_max, d_min` (price-responsive demand) + +Each file declares `BUS_COUNT`, `VOLTAGE_LEVEL`, `SOURCE` and `DESCRIPTION` as class-level metadata. The values below are reproduced verbatim from those declarations (so the file itself is the source of truth): + + +| File | Voltage | Buses | `SOURCE` | `DESCRIPTION` | +| -------------------------------- | ------- | ----- | -------- | ------------------------------------------------------------------ | +| `transmission/Case5.py` | HV | 5 | MATPOWER | IEEE 5-bus test system | +| `transmission/Case14.py` | HV | 14 | MATPOWER | IEEE 14-bus test system | +| `transmission/Case29GB.py` | HV | 29 | custom | GB reduced 29-bus transmission network | +| `transmission/Case118.py` | HV | 118 | MATPOWER | IEEE 118-bus test system | +| `transmission/Case300.py` | HV | 300 | MATPOWER | IEEE 300-bus test system | +| `transmission/Case552GB.py` | HV | 552 | GB | Great Britain 552-bus transmission (distinct from 29-bus Case29GB) | +| `transmission/Case1354pegase.py` | HV | 1354 | MATPOWER | European PEGASE 1354-bus system | +| `transmission/Case2383wp.py` | HV | 2383 | MATPOWER | Polish 2383-bus winter peak system | +| `distribution/Case33bw.py` | MV | 33 | MATPOWER | IEEE 33-bus Baran & Wu radial distribution | +| `distribution/Case118zh.py` | MV | 118 | MATPOWER | 118-bus Zhang distribution system | +| `distribution/Case123.py` | MV | 123 | MATPOWER | IEEE 123-bus three-phase distribution | +| `distribution/Case141.py` | MV | 141 | MATPOWER | 141-bus Caracas distribution system (Khodr et al., EPSR 2008) | +| `distribution/Case533mt_hi.py` | MV | 533 | MATPOWER | 533-bus Swedish distribution (high load) | +| `distribution/Case533mt_lo.py` | MV | 533 | MATPOWER | 533-bus Swedish distribution (low load) | + + +--- + +## 3. Loading + +### 3.1 Direct parquet load (no extra dependency on PowerZoo) + +```python +import pandas as pd +from huggingface_hub import hf_hub_download + +path = hf_hub_download( + repo_id="PowerZooJax/PowerZooDataset", + repo_type="dataset", + filename="parquet/AEMO_5min_Demand_2025_2026.parquet", +) +df = pd.read_parquet(path) +print(df.head()) +``` + +### 3.2 Via `datasets` (per-config) + +```python +from datasets import load_dataset + +ds = load_dataset( + "PowerZooJax/PowerZooDataset", + name="aemo_5min_demand", + split="train", +) +``` + +### 3.3 Via the PowerZooJax `DataLoader` + +If you have the (separately released) benchmark package installed, instantiate `DataLoader` with this repository's `parquet/` and `manifests/` directories: + +```python +from powerzoojax.data import DataLoader + +loader = DataLoader( + data_dir="/path/to/PowerZooDataset/parquet", + manifest_dir="/path/to/PowerZooDataset/manifests", +) +print(loader.list_available_datasets()) +df = loader.load_actual_series("aemo_5min_demand") +``` + +### 3.4 Power-grid cases + +```python +from powerzoo.case.distribution.Case141 import Case141 +case = Case141() +case.check() +case.get_node_ptdf() +``` + +--- + +## 4. Schema conventions + +- **Time stamps.** Calendar-mode parquet files store timestamps as `datetime64[ns, UTC]`, with the exception of `GB_NESO_Demand_2009_2025_30min.parquet`, which uses two columns (`SETTLEMENT_DATE` + `SETTLEMENT_PERIOD`) — see the `datetime_recipe` in `manifests/gb_neso_demand.json`. The Ausgrid metadata explicitly declares `timezone_local = "Australia/Sydney"` and `timezone_stored = "UTC"`; for the other calendar sources, only the stored UTC representation is documented in metadata. +- **Profile-mode traces.** The data-centre traces (Alibaba / Azure / Google) are tagged `time_mode = "profile"` and `cyclical = true` in their manifests, anchored to a `data_epoch` (Alibaba DC: `2018-01-06`, Alibaba GPU: `2020-07-01`, Azure: `2019-01-01`, Google: `2019-05-01`). They are intended as periodic exogenous signals, not absolute calendar series. +- **Imputation.** `Ausgrid_Zone_Substation_FY25_imputed_15min.parquet` contains imputed values (as indicated by its filename suffix and source path); the imputation method is not documented inside the metadata shipped here. Users requiring raw observations should pull from the upstream Ausgrid release. +- **Units.** Power columns in the parquet traces are in MW. The GB market-mid file uses prices in `mid_price_`* columns (the upstream Elexon convention is £/MWh; consult the source URL for any unit caveats). Data-centre utilisation columns are 0–100 (percent) before the manifest's `normalize` factor is applied. + +--- + +## 5. Source acknowledgements & licensing + +This repository **redistributes derivative datasets** built from publicly accessible upstream releases. Each upstream is governed by its own terms; users are responsible for complying with them. The `source_url` and `source_organization` fields in every `parquet/*.json` and `manifests/*.json` give the canonical pointer. + + +| Trace | Upstream | Original portal | +| ------------------------------------- | -------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| AEMO 5-min demand & POE forecasts | Australian Energy Market Operator | [https://visualisations.aemo.com.au/aemo/nemweb/](https://visualisations.aemo.com.au/aemo/nemweb/) | +| Ausgrid zone-substation load | Ausgrid | [https://www.ausgrid.com.au/Industry/Our-Research/Data-to-share/Distribution-zone-substation-data](https://www.ausgrid.com.au/Industry/Our-Research/Data-to-share/Distribution-zone-substation-data) | +| GB demand actual & day-ahead forecast | Elexon (BMRS) | [https://data.elexon.co.uk/bmrs/api/v1](https://data.elexon.co.uk/bmrs/api/v1) | +| GB generation by fuel type | Elexon (BMRS) | [https://data.elexon.co.uk/bmrs/api/v1/generation/actual/per-type](https://data.elexon.co.uk/bmrs/api/v1/generation/actual/per-type) | +| GB historical demand 2009–2025 | National Energy System Operator (NESO) | [https://www.neso.energy/data-portal/historic-demand-data](https://www.neso.energy/data-portal/historic-demand-data) | +| Alibaba cluster trace 2018 | Alibaba Group | [https://github.com/alibaba/clusterdata/tree/master/cluster-trace-v2018](https://github.com/alibaba/clusterdata/tree/master/cluster-trace-v2018) | +| Alibaba GPU trace 2020 | Alibaba Group | [https://github.com/alibaba/clusterdata/tree/master/cluster-trace-gpu-v2020](https://github.com/alibaba/clusterdata/tree/master/cluster-trace-gpu-v2020) | +| Azure public dataset v2 | Microsoft | [https://github.com/Azure/AzurePublicDataset](https://github.com/Azure/AzurePublicDataset) | +| Google cluster data 2019 | Google | [https://github.com/google/cluster-data](https://github.com/google/cluster-data) | + + +The packaging artefacts authored for this benchmark (the manifest schema, case-file Python representations, schema harmonisation logic) are intended to be released under a permissive open-source licence at camera-ready time; the underlying parquet data inherits the upstream licence in every case. **Do not assume any single licence applies to the data themselves.** When in doubt, redownload from the upstream URL above and treat that copy as authoritative. + +No personally identifiable information is present in any trace; demand and generation series are aggregated at substation, regional or national level. + +--- + +## 6. Intended use & limitations + +- **Intended use.** Reinforcement-learning research, load / generation forecasting, market-clearing simulation, OPF benchmarking, distribution-system control, data-centre power-shaping research, demand-response studies. +- **Out-of-scope.** Short-term operational decisions for real grids, retail tariff design, settlement of real markets. The forecasts and prices included are historical educational artefacts, not signals for live trading. +- **Known limitations.** + - Several calendar-mode traces extend slightly past the `date_range` declared in their manifest (e.g. AEMO 5-min runs through 2026-02-12; GB demand/generation through April 2026). The manifest `date_range` is a planning bound, not a strict assertion of file extent — consult the parquet itself for the authoritative range. + - The Ausgrid trace is imputed; the imputation procedure is not documented in this repository. + - The data-centre traces are stored at 5-minute (300 s) resolution. The upstream releases provide additional fields and finer resolutions; this repository ships only the columns mapped by each manifest. + - The grid-case files use parameters consistent with the cited source systems but are not guaranteed to be byte-identical to any specific MATPOWER / IEEE PES / PEGASE release; they should not be used for compliance studies of real networks. + +--- + +## 7. File integrity + +To regenerate provenance metadata locally: + +```bash +python -c " +import pyarrow.parquet as pq, glob, os +for p in sorted(glob.glob('parquet/*.parquet')): + m = pq.read_metadata(p) + print(f'{os.path.basename(p):60s} rows={m.num_rows:>10,} cols={m.num_columns:>3} bytes={os.path.getsize(p):>10,}') +" +``` + +Expected output is reproduced in §2.1. + +--- + +## 8. Changelog + +- **v0.1 (***)** — initial public release: 11 harmonised parquet traces, 11 loader manifests, 14 grid-case files (8 transmission + 6 distribution). + diff --git a/manifests/aemo_5min_demand.json b/manifests/aemo_5min_demand.json new file mode 100644 index 0000000000000000000000000000000000000000..526669821cfd4493d48511e9b889512a9b8280f3 --- /dev/null +++ b/manifests/aemo_5min_demand.json @@ -0,0 +1,24 @@ +{ + "name": "aemo_5min_demand", + "source": "aemo", + "data_type": "actual_series", + "time_mode": "calendar", + "resolution": "5min", + "parquet_file": "AEMO_5min_Demand_2025_2026.parquet", + "metadata_json": "AEMO_5min_Demand_2025_2026.json", + "column_map": { + "OPERATIONAL_DEMAND": "load.actual_mw" + }, + "index_map": { + "INTERVAL_DATETIME": "datetime", + "REGIONID": "region" + }, + "derived": {}, + "normalize": {}, + "data_epoch": null, + "cyclical": false, + "region_values": ["NSW1", "QLD1", "SA1", "TAS1", "VIC1"], + "date_range": ["2024-09-18", "2026-12-31"], + "source_url": "https://visualisations.aemo.com.au/aemo/nemweb/index.html#", + "source_organization": "Australian Energy Market Operator (AEMO)" +} diff --git a/manifests/aemo_forecast.json b/manifests/aemo_forecast.json new file mode 100644 index 0000000000000000000000000000000000000000..ca0b71200ebe651d41fda09737d70d7c36767e5e --- /dev/null +++ b/manifests/aemo_forecast.json @@ -0,0 +1,28 @@ +{ + "name": "aemo_forecast", + "source": "aemo", + "data_type": "forecast_panel", + "time_mode": "calendar", + "resolution": "30min", + "parquet_file": "AEMO_Forecast_vs_Actual_2025.parquet", + "metadata_json": "AEMO_Forecast_vs_Actual_2025.json", + "column_map": { + "OPERATIONAL_DEMAND_POE10": "load.forecast_p10_mw", + "OPERATIONAL_DEMAND_POE50": "load.forecast_p50_mw", + "OPERATIONAL_DEMAND_POE90": "load.forecast_p90_mw", + "OPERATIONAL_DEMAND": "load.actual_mw" + }, + "index_map": { + "REGIONID": "region", + "FORECAST_DATETIME": "issue_time", + "INTERVAL_DATETIME": "target_time" + }, + "derived": {}, + "normalize": {}, + "data_epoch": null, + "cyclical": false, + "region_values": ["NSW1", "QLD1", "SA1", "TAS1", "VIC1"], + "date_range": ["2025-01-26", "2025-12-31"], + "source_url": "https://visualisations.aemo.com.au/aemo/nemweb/index.html#", + "source_organization": "Australian Energy Market Operator (AEMO)" +} diff --git a/manifests/alibaba_dc_2018.json b/manifests/alibaba_dc_2018.json new file mode 100644 index 0000000000000000000000000000000000000000..c3585157a7d0a4afd2cc49b4ce2355e5b65ef94b --- /dev/null +++ b/manifests/alibaba_dc_2018.json @@ -0,0 +1,33 @@ +{ + "name": "alibaba_dc_2018", + "source": "alibaba", + "data_type": "actual_series", + "time_mode": "profile", + "resolution": "300s", + "parquet_file": "alibaba_dc_2018_300s.parquet", + "column_map": { + "cpu_util_percent": "datacenter.cpu_util", + "mem_util_percent": "datacenter.mem_util", + "net_in": "datacenter.net_in", + "net_out": "datacenter.net_out", + "disk_io_percent": "datacenter.disk_io" + }, + "index_map": { + "time_stamp": "datetime" + }, + "derived": {}, + "normalize": { + "datacenter.cpu_util": 100, + "datacenter.mem_util": 100, + "datacenter.net_in": 100, + "datacenter.net_out": 100, + "datacenter.disk_io": 100 + }, + "data_epoch": "2018-01-06T00:00:00", + "cyclical": true, + "region_values": [], + "date_range": null, + "metadata_json": null, + "source_url": "https://github.com/alibaba/clusterdata/tree/master/cluster-trace-v2018", + "source_organization": "Alibaba Group" +} diff --git a/manifests/alibaba_gpu_2020.json b/manifests/alibaba_gpu_2020.json new file mode 100644 index 0000000000000000000000000000000000000000..435f7e3792fb6d0a676443c206fe2b87c5375d1d --- /dev/null +++ b/manifests/alibaba_gpu_2020.json @@ -0,0 +1,27 @@ +{ + "name": "alibaba_gpu_2020", + "source": "alibaba", + "data_type": "actual_series", + "time_mode": "profile", + "resolution": "300s", + "parquet_file": "alibaba_gpu_2020_300s.parquet", + "column_map": { + "gpu_util_percent": "datacenter.gpu_util", + "cpu_util_percent": "datacenter.cpu_util" + }, + "index_map": { + "time_stamp": "datetime" + }, + "derived": {}, + "normalize": { + "datacenter.gpu_util": 100, + "datacenter.cpu_util": 100 + }, + "data_epoch": "2020-07-01T00:00:00", + "cyclical": true, + "region_values": [], + "date_range": null, + "metadata_json": null, + "source_url": "https://github.com/alibaba/clusterdata/tree/master/cluster-trace-gpu-v2020", + "source_organization": "Alibaba Group" +} diff --git a/manifests/ausgrid_zone_substation_fy25_imputed.json b/manifests/ausgrid_zone_substation_fy25_imputed.json new file mode 100644 index 0000000000000000000000000000000000000000..ae8cfde91bb75e18ec5fb06f1120b7686dae82d9 --- /dev/null +++ b/manifests/ausgrid_zone_substation_fy25_imputed.json @@ -0,0 +1,203 @@ +{ + "name": "ausgrid_zone_substation_fy25_imputed", + "source": "ausgrid", + "data_type": "actual_series", + "time_mode": "calendar", + "resolution": "15min", + "parquet_file": "Ausgrid_Zone_Substation_FY25_imputed_15min.parquet", + "column_map": { + "load_mw": "load.actual_mw" + }, + "index_map": { + "interval_start": "datetime", + "zone_substation": "region" + }, + "derived": {}, + "normalize": {}, + "data_epoch": null, + "cyclical": false, + "region_values": [ + "Aberdeen 66_11kV", + "Adamstown 132_11kV", + "Argenton 132_11kV", + "Auburn 33_11kV", + "Avoca 66_11kV", + "Avondale 33_11kV", + "Baerami 33_11kV", + "Balgowlah North 132_11kV", + "Bankstown 132_11kV", + "Bass Hill 33_11kV", + "Beacon Hill 33_11kV", + "Belmore Park 132_11kV", + "Belrose 33_11kV", + "Berkeley Vale 132_11kV", + "Berowra 132_11kV", + "Blakehurst 33_11kV", + "Botany 33_11kV", + "Brandy Hill 132_11kV", + "Branxton 66_11kV", + "Broadmeadow 132_11kV", + "Brookvale 33_11kV", + "Burwood 132_11kV", + "Campbell St 132_11kV", + "Camperdown 33_11kV", + "Campsie 33_11kV", + "Cardiff 33_11kV", + "Careel Bay 33_11kV", + "Caringbah 33_11kV", + "Castle Cove 132_11kV", + "Cessnock South 33_11kV", + "Charlestown 132_11kV", + "Charmhaven 132_11kV", + "Chatswood 33_11kV", + "City Central 132_11kV", + "City North 132_11kV", + "City South 132_11kV", + "Clovelly 132_11kV", + "Concord 33_11kV", + "Cronulla 132_11kV", + "Croudace Bay 33_11kV", + "Crows Nest 132_11kV", + "Croydon 132_11kV", + "Dalley St 132_11kV", + "Darling Harbour 132_11kV", + "Darlinghurst 33_11kV", + "Dee Why West 33_11kV", + "Denman 66_11kV", + "Double Bay 132_11kV", + "Drummoyne 132_11kV", + "Edgeworth 33_11kV", + "Empire Bay 66_11kV", + "Engadine 132_11kV", + "Epping 66_11kV", + "Erina 66_11kV", + "Flemington 132_11kV", + "Galston 132_11kV", + "Gateshead 33_11kV", + "Gore Hill 33_11kV", + "Green Square 132_11kV", + "Greenacre 132_11kV", + "Gwawley Bay 132_11kV", + "Harbord 33_11kV", + "Homebush Bay 132_11kV", + "Hornsby 132_11kV", + "Hunters Hill 66_11kV", + "Hurstville North 132_11kV", + "Jannali 33_11kV", + "Jesmond 132_11kV", + "Jewells 33_11kV", + "Killarney 33_11kV", + "Kingsford 132_11kV", + "Kirrawee 132_11kV", + "Kogarah 132_11kV", + "Kotara 33_11kV", + "Kurnell South 132_11kV", + "Kurri 132_11kV", + "Lake Munmorah 132_11kV", + "Leichhardt 132_11kV", + "Leightonfield 33_11kV", + "Lemington 66_11kV", + "Lidcombe 33_11kV", + "Lindfield 33_11kV", + "Lisarow 33_11kV", + "Long Jetty 66_11kV", + "Lucas Heights 33_11kV", + "Macquarie Park 132_11kV", + "Maitland 33_11kV", + "Manly 33_11kV", + "Maroubra 132_11kV", + "Marrickville 132_11kV", + "Maryland 132_11kV", + "Mascot 33_11kV", + "Matraville 33_11kV", + "Mayfield West 132_11kV", + "Meadowbank 132_11kV", + "Medowie 33_11kV", + "Menai 132_11kV", + "Merriwa 33_11kV", + "Metford 33_11kV", + "Milperra 132_11kV", + "Miranda 33_11kV", + "Mitchell Line 66_11kV", + "Mitchells Flat 66_11kV", + "Mona Vale 33_11kV", + "Moonan 33_11kV", + "Morisset 132_11kV", + "Mortdale 33_11kV", + "Mosman 132_11kV", + "Mt Hutton 33_11kV", + "Mt Thorley 66_11kV", + "Muswellbrook 33_11kV", + "Narrabeen 33_11kV", + "Nelson Bay 33_11kV", + "New Lambton 33_11kV", + 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"azure", + "data_type": "actual_series", + "time_mode": "profile", + "resolution": "300s", + "parquet_file": "azure_dc_v2_300s.parquet", + "column_map": { + "cpu_usage": "datacenter.cpu_util", + "assigned_mem": "datacenter.mem_util" + }, + "index_map": { + "time_stamp": "datetime" + }, + "derived": {}, + "normalize": {}, + "data_epoch": "2019-01-01T00:00:00", + "cyclical": true, + "region_values": [], + "date_range": null, + "metadata_json": null, + "source_url": "https://github.com/Azure/AzurePublicDataset/blob/master/AzurePublicDatasetV2.md", + "source_organization": "Microsoft Corporation" +} diff --git a/manifests/gb_forecast_actual_demand.json b/manifests/gb_forecast_actual_demand.json new file mode 100644 index 0000000000000000000000000000000000000000..f0bd1d9b0db8d8cc00c820cbb5a3978cb1b3ee01 --- /dev/null +++ b/manifests/gb_forecast_actual_demand.json @@ -0,0 +1,27 @@ +{ + "name": "gb_forecast_actual_demand", + "source": "gb", + "data_type": "actual_series", + "time_mode": "calendar", + "resolution": "30min", + "parquet_file": "GB_Forecast_Actual_Demand_2023_2025_30min.parquet", + "column_map": { + "Actual": "load.actual_mw", + "DAForecast": "load.forecast_da_mw" + }, + "index_map": { + "startTime": "datetime" + }, + "derived": {}, + "normalize": {}, + "data_epoch": null, + "cyclical": false, + "region_values": [], + "date_range": ["2023-07-05", "2026-04-05"], + "metadata_json": "GB_Forecast_Actual_Demand_2023_2025_30min.json", + "source_urls": [ + "https://data.elexon.co.uk/bmrs/api/v1/demand/actual/total", + "https://data.elexon.co.uk/bmrs/api/v1/forecast/demand/total/day-ahead" + ], + "source_organization": "Elexon Limited" +} diff --git a/manifests/gb_gen_by_type.json b/manifests/gb_gen_by_type.json new file mode 100644 index 0000000000000000000000000000000000000000..3ace29499fc3145fde6a092bb31fae3b5fc722dc --- /dev/null +++ b/manifests/gb_gen_by_type.json @@ -0,0 +1,25 @@ +{ + "name": "gb_gen_by_type", + "source": "gb", + "data_type": 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"30min", + "parquet_file": "MID_GB_30min_aligned_to_gen.parquet", + "column_map": { + "mid_price_APXMIDP": "market.mid_price_apx", + "mid_price_N2EXMIDP": "market.mid_price_n2ex", + "mid_volume_APXMIDP": "market.mid_volume_apx", + "mid_volume_N2EXMIDP": "market.mid_volume_n2ex" + }, + "index_map": { + "startTime": "datetime" + }, + "derived": {}, + "normalize": {}, + "data_epoch": null, + "cyclical": false, + "region_values": [], + "date_range": ["2023-07-05", "2026-04-05"], + "metadata_json": "MID_GB_30min_aligned_to_gen.json" +} diff --git a/manifests/gb_neso_demand.json b/manifests/gb_neso_demand.json new file mode 100644 index 0000000000000000000000000000000000000000..f059552e75fafe495db136a079558403d90d8ca9 --- /dev/null +++ b/manifests/gb_neso_demand.json @@ -0,0 +1,44 @@ +{ + "name": "gb_neso_demand", + "source": "gb", + "data_type": "actual_series", + "time_mode": "calendar", + "resolution": "30min", + "parquet_file": "GB_NESO_Demand_2009_2025_30min.parquet", + "metadata_json": 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index 0000000000000000000000000000000000000000..58b476f4627d06623721859abb4b9b8b74dc2e2f --- /dev/null +++ b/parquet/google_dc_2019_300s.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6fe98aa4249301749505d97f1b2b0801496d2a7fa81e76b767cd7234a0970223 +size 359554 diff --git a/powergrid_case/CaseBase.py b/powergrid_case/CaseBase.py new file mode 100644 index 0000000000000000000000000000000000000000..3c9ae2bcc8c0079a9dc7084db80643930798d08f --- /dev/null +++ b/powergrid_case/CaseBase.py @@ -0,0 +1,602 @@ +"""Power market case base module + +This module contains basic data structures and computation methods for power market simulation. +""" +from typing import List, Union +import pandas as pd +import numpy as np +from scipy.sparse import coo_matrix +import scipy.sparse as sp + + +class DataFrame(pd.DataFrame): + """Extended DataFrame for power market data display + + Inherits from pandas.DataFrame with label feature and custom display format. + """ + + def __init__(self, columns: List[str], data: Union[List, np.ndarray]): + """Initialize DataFrame + + Args: + columns: column names + data: data content + """ + super(DataFrame, self).__init__(data=data, columns=columns) + self.loc[:, '#id'] = self.index + self.index = self['id'] + self.label = '' + + def __repr__(self) -> str: + """Custom string representation""" + return f'{"=" * 20} {self.label} {"=" * 20}\n{self.to_string(index=False)}' + + def __str__(self) -> str: + """String representation""" + return self.__repr__() + + def set_label(self, label: str) -> 'DataFrame': + """Set label + + Args: + label: label name + + Returns: + self to support method chaining + """ + self.label = label + return self + + +class ClearCase(object): + """Base class for power market clearing cases + + Contains basic data for nodes, units, lines and loads, + along with matrix computations and data processing methods. + + Subclasses should override the class-level metadata attributes below + to enable automatic discovery, filtering, and compatibility validation. + """ + + GRID_TYPE: str = "" + BUS_COUNT: int = 0 + PHASE: str = "1" + VOLTAGE_LEVEL: str = "" + SOURCE: str = "" + DESCRIPTION: str = "" + + def __init__(self, mock=True): + """Initialize clearing case""" + self.init_flag = False + self._node_gsdf = None + self._node_ptdf = None + self._plotter = None + self.mocker = None + self.nodes_map_units = None + self.flexloads_num = len(getattr(self, 'flexloads', [])) + if mock: + from .CaseMocker import CaseMocker + self.mocker, _ = CaseMocker(self).mock_c() + + # if lines['cap'] == 0 or lines['floor'], set to 1000000 + self.lines.loc[self.lines['cap'] == 0, 'cap'] = 1000000 + self.lines.loc[self.lines['floor'] == 0, 'floor'] = -1000000 + + def init(self) -> 'ClearCase': + """Initialize case data + + Set node ID mapping and basic flags. + + Returns: + self to support method chaining + """ + self.init_flag = True + self.units['#bus_id'], self.loads['#bus_id'] = self.get_nodes_id( + self.units['bus_id'], self.loads['bus_id'] + ) + if self.flexloads_num > 0: + # The trailing comma is required because the function returns a list object which needs ',' unpacking. + self.flexloads['#bus_id'], = self.get_nodes_id(self.flexloads['bus_id']) + self.lines['#from'], self.lines['#to'] = self.get_nodes_id( + self.lines['from'], self.lines['to']) + if not hasattr(self, 'name'): + self.name = 'Case' + return self + + def __repr__(self) -> str: + """String representation""" + return '\n'.join(self.to_str()) + + # ============================================================================= + # Plotter property + # ============================================================================= + + @property + def plotter(self): + """Get the CasePlotter instance (lazy initialization) + + Returns: + CasePlotter instance for visualizing this case + """ + if self._plotter is None: + from .CasePlotter import CasePlotter + self._plotter = CasePlotter(self) + return self._plotter + + # ============================================================================= + # Data validation methods + # ============================================================================= + + def check(self) -> None: + """Check data integrity + + Verify that each table contains the required columns. + + Raises: + AssertionError: raised when required columns are missing + """ + nodes_col = {'id'} + units_col = {'id', 'bus_id', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min'} + lines_col = {'id', 'from', 'to', 'x', 'floor', 'cap'} + loads_col = {'id', 'bus_id', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'} + + self.assert_cols(nodes_col, getattr(self, "nodes")) + self.assert_cols(units_col, getattr(self, "units")) + self.assert_cols(lines_col, getattr(self, "lines")) + self.assert_cols(loads_col, getattr(self, "loads")) + + @staticmethod + def assert_cols(min_col_set: set, df_to_check: pd.DataFrame) -> None: + """Assert that a DataFrame contains at least a set of columns + + Args: + min_col_set: minimal required column set + df_to_check: DataFrame to check + + Raises: + AssertionError: raised when required columns are missing + """ + assert set(df_to_check.columns) & min_col_set == min_col_set, \ + f'最少需要以下列：{min_col_set}' + + def get_nodes_id(self, *args) -> List[np.ndarray]: + """Get node ID mapping + + Args: + *args: node ID arrays + + Returns: + list of mapped node IDs + """ + return [self.nodes.loc[np.array(a).flatten(), '#id'].values for a in args] + + # ============================================================================= + # Matrix computation methods + # ============================================================================= + + def get_node_gsdf(self) -> pd.DataFrame: + """Get node GSDF matrix (cached) + + Returns: + generation shift distribution factor matrix per node + """ + if self._node_gsdf is None: + self.cal_gsdf(False) + self._node_gsdf = self.node_gsdf + return self._node_gsdf + + def get_node_ptdf(self) -> pd.DataFrame: + """Get node PTDF matrix (cached) + + Returns: + power transfer distribution factor matrix per node + """ + if self._node_ptdf is None: + self.cal_gsdf(True) + self._node_ptdf = self.node_ptdf + return self._node_ptdf + + def cal_gsdf(self, ptdf: bool = False) -> 'ClearCase': + """Compute GSDF and optionally PTDF matrices + + Args: + ptdf: whether to compute PTDF matrices as well + + Returns: + self to support method chaining + """ + if not hasattr(self, 'init_flag') or not self.init_flag: + self.init() + + # Build line-node incidence matrix + lines_nodes = coo_matrix( + (np.repeat((1, -1), len(self.lines)), + (np.tile(np.arange(len(self.lines)), 2), + self.lines[['#from', '#to']].values.T.flatten())) + ).toarray() + + # Line susceptance matrix + lines_B = np.diag(-1 / self.lines['x']) + + # Node admittance matrix (excluding reference node) + self.node_Y = lines_nodes.T.dot(lines_B).dot(lines_nodes)[1:, 1:] + node_Y_inv = np.linalg.inv(self.node_Y) + + # Compute GSDF matrix + node_gsdf_1 = lines_B.dot(lines_nodes.dot( + np.vstack((np.zeros(len(self.nodes) - 1), node_Y_inv)) + )) + self.node_gsdf = pd.DataFrame( + np.hstack((np.zeros((len(self.lines), 1)), node_gsdf_1)), + index=self.lines['id'], + columns=self.nodes['id'] + ) + + # GSDF matrices for units and loads + self.unit_gsdf = self.node_gsdf[self.units['bus_id']] + self.unit_load_gsdf = pd.concat(( + self.node_gsdf[self.units['bus_id']], + -self.node_gsdf[self.loads['bus_id']] + ), axis=1) + + # Compute PTDF matrix (only for constrained lines) + if ptdf: + self.ptdf_lines_flag = np.where( + (self.lines.loc[:, 'floor'] == 0) & (self.lines.loc[:, 'cap'] == 0), + False, True + ) + self.ptdf_lines = self.lines.loc[self.ptdf_lines_flag] + self.node_ptdf = self.node_gsdf[self.ptdf_lines_flag] + self.unit_load_ptdf = pd.concat(( + self.node_ptdf[self.units['bus_id']], + -self.node_ptdf[self.loads['bus_id']] + ), axis=1) + return self + + def get_A_matrix(self) -> np.ndarray: + """Get adjacency matrix + + Returns: + network adjacency matrix + """ + if not hasattr(self, 'init_flag') or not self.init_flag: + self.init() + row = np.hstack((self.lines['#from'], self.lines['#to'])) + col = np.hstack((self.lines['#to'], self.lines['#from'])) + A = coo_matrix( + (np.ones(len(row)), (row, col)), + shape=(len(self.nodes), len(self.nodes)) + ).toarray() + return A + + def get_D_matrix(self) -> np.ndarray: + """Get degree matrix + + Returns: + diagonal degree matrix whose diagonal is node degrees + """ + if not hasattr(self, 'init_flag') or not self.init_flag: + self.init() + A = self.get_A_matrix() + d = np.sum(A, axis=1) + D = np.diag(d) + return D + + def normalize_adjacency(self, adjacency: np.ndarray) -> np.ndarray: + """Normalize adjacency matrix + + Args: + adjacency: adjacency matrix + + Returns: + normalized adjacency matrix + """ + adj = sp.coo_matrix(adjacency) + rowsum = np.array(adj.sum(1)) # node degree per row + rowsum[rowsum == 0] = 1 # avoid division by zero + degree_mat_inv_sqrt = sp.diags(np.power(rowsum, -0.5).flatten()) + normalized_adjacency = adj.dot(degree_mat_inv_sqrt).transpose().dot(degree_mat_inv_sqrt).tocoo() + return normalized_adjacency.todense() + + def get_L_matrix(self) -> np.ndarray: + """Get normalized Laplacian matrix + + Returns: + normalized Laplacian matrix + """ + if not hasattr(self, 'init_flag') or not self.init_flag: + self.init() + A = self.get_A_matrix() + A_self = A + np.eye(len(A)) + D_half_inv = np.diag(np.power(np.sum(A_self, axis=1), -0.5)) + L = np.eye(A_self.shape[0]) - np.dot(np.dot(D_half_inv, A_self), D_half_inv) + return L + + # ============================================================================= + # Node mapping methods + # ============================================================================= + + def get_nodes_map_units_and_loads(self) -> np.ndarray: + """Get node-to-units and node-to-loads mapping matrix + + Returns: + mapping matrix (units positive, loads negative) + """ + if not hasattr(self, 'init_flag') or not self.init_flag: + self.init() + + # Node-to-unit relationship + self.nodes_map_units = coo_matrix( + (np.ones(len(self.units)), (self.units['#bus_id'], self.units['#id'])), + shape=(len(self.nodes), len(self.units)) + ).toarray() + + # Node-to-load relationship + self.nodes_map_loads = coo_matrix( + (np.ones(len(self.loads)), (self.loads['#bus_id'], self.loads['#id'])), + shape=(len(self.nodes), len(self.loads)) + ).toarray() + + return np.hstack([self.nodes_map_units, -self.nodes_map_loads]) + + def get_nodes_units_map(self) -> np.ndarray: + """Get node-to-units mapping matrix + + Returns: + node-to-units mapping matrix + """ + if not hasattr(self, 'init_flag') or not self.init_flag: + self.init() + + self.nodes_map_units = coo_matrix( + (np.ones(len(self.units)), (self.units['#bus_id'], self.units['#id'])), + shape=(len(self.nodes), len(self.units)) + ).toarray() + return self.nodes_map_units + + def get_nodes_loads_map(self) -> np.ndarray: + """Get node-to-loads mapping matrix + + Returns: + node-to-loads mapping matrix + """ + if not hasattr(self, 'init_flag') or not self.init_flag: + self.init() + + self.nodes_map_loads = coo_matrix( + (np.ones(len(self.loads)), (self.loads['#bus_id'], self.loads['#id'])), + shape=(len(self.nodes), len(self.loads)) + ).toarray() + return self.nodes_map_loads + + def get_nodes_flexloads_map(self) -> np.ndarray: + """Get node-to-flexloads mapping matrix + + Returns: + node-to-flexloads mapping matrix + """ + if not hasattr(self, 'init_flag') or not self.init_flag: + self.init() + + self.nodes_map_flexloads = coo_matrix( + (np.ones(len(self.flexloads)), (self.flexloads['#bus_id'], self.flexloads['#id'])), + shape=(len(self.nodes), len(self.flexloads)) + ).toarray() + return self.nodes_map_flexloads + + # ============================================================================= + # Utility methods + # ============================================================================= + + def length(self) -> List[int]: + """Get lengths of each data table + + Returns: + [nodes, units, lines, loads] + """ + return [len(getattr(self, v)) for v in ["nodes", "units", "lines", "loads"]] + + def to_str(self) -> List[str]: + """Convert to string representation + + Returns: + list of string representations of tables + """ + v_list = [getattr(self, v).set_label(v) for v in ["nodes", "units", "lines", "loads"]] + v_str_list = [str(v) for v in v_list] + return v_str_list + + # ============================================================================= + # Cost calculation methods + # ============================================================================= + def cal_unit_piecewise_by_margin_cost(self, band_num: int = 5) -> np.ndarray: + """Compute piecewise linear parameters based on marginal cost + + Args: + band_num: number of segments + + Returns: + piecewise cost matrix + """ + a, b, c = self.units['mc_a'], self.units['mc_b'], self.units['mc_c'] + p_max, p_min = self.units['p_max'], self.units['p_min'] + + # Compute segment ratios + xs = np.tile((p_max - p_min) / p_max / band_num, (band_num, 1)).T + ys = [] + + # Compute marginal cost per segment + for x in np.cumsum(xs, 1).T: + y = list(a * (p_min + p_max * x) ** 2 + b * (p_min + p_max * x) + c) + # Ensure costs are monotonically increasing + if len(ys) > 0: + for i in range(len(y)): + if y[i] <= ys[-1][i]: + y[i] = ys[-1][i] + 1 + ys.append(y) + + return np.array(ys).T + + def cal_units_cost(self, units_power: Union[List, np.ndarray]) -> np.ndarray: + """Compute generation cost for units + + Args: + units_power: unit output array + + Returns: + unit generation cost array + """ + units_power = np.array(units_power) if isinstance(units_power, list) else units_power + units_cost = ( + (self.units['mc_a'].values / 3) * units_power ** 3 + + (self.units['mc_b'].values / 2) * units_power ** 2 + + self.units['mc_c'].values * units_power + ) + return units_cost + + # ============================================================================= + # Graph connectivity methods + # ============================================================================= + + def is_connected_graph(self) -> bool: + """Check if the power network forms a connected graph. + + Returns: + True if the graph is connected, False otherwise + """ + return len(self.get_graph_components()) <= 1 + + def get_graph_components(self) -> List[List]: + """Get all connected components of the power network graph. + + Only in-service lines (status == 1, or missing status column) are + considered. + + Returns: + List of connected components, each component is a list of node IDs + """ + if len(self.nodes) == 0: + return [] + + adjacency: dict = {node_id: [] for node_id in self.nodes['id'].values} + + for _, line in self.lines.iterrows(): + if line.get('status', 1) == 1: + from_bus, to_bus = line['from'], line['to'] + adjacency[from_bus].append(to_bus) + adjacency[to_bus].append(from_bus) + + visited: set = set() + components: List[List] = [] + + for node_id in self.nodes['id'].values: + if node_id not in visited: + component = [] + queue = [node_id] + visited.add(node_id) + while queue: + current = queue.pop(0) + component.append(current) + for neighbor in adjacency[current]: + if neighbor not in visited: + visited.add(neighbor) + queue.append(neighbor) + components.append(component) + + return components + + def get_3ph_matrix(self, config: pd.Series, matrix_type: str = 'Z') -> np.ndarray: + """Extract 3x3 matrix from line configuration + + For three-phase systems, extract impedance (Z), capacitance (C), or other + 3x3 matrices from line configuration data. + + Args: + config: Line configuration series with elements like Z11, Z12, ..., Z33 + matrix_type: Type of matrix to extract ('Z' for impedance, 'C' for capacitance, etc.) + + Returns: + 3x3 numpy array (complex128 for 'Z', float64 for others) + + Raises: + AttributeError: If line_config does not exist for this case + KeyError: If required matrix elements are not in config + + Example: + >>> config = case.line_config.iloc[0] + >>> z_matrix = case.get_3ph_matrix(config, 'Z') + >>> z_matrix.shape + (3, 3) + """ + if not hasattr(self, 'line_config'): + raise AttributeError( + f"Case {self.name} does not have 'line_config' attribute. " + "This method is only available for three-phase cases." + ) + + # Create matrix with appropriate data type + dtype = np.complex128 if matrix_type == 'Z' else np.float64 + + # Generate all element names: Z11, Z12, ..., Z33 + element_names = [f'{matrix_type}{i + 1}{j + 1}' for i in range(3) for j in range(3)] + + # Validate all elements exist (fail fast) + missing_elements = [name for name in element_names if name not in config.index] + if missing_elements: + raise KeyError( + f"Elements {missing_elements} not found in config. " + f"Available elements: {list(config.index)}" + ) + + # Extract values and reshape to 3x3 matrix (vectorized) + matrix_3x3 = np.array([config[name] for name in element_names], dtype=dtype).reshape(3, 3) + + return matrix_3x3 + + def get_line_impedance_matrices(self, reshape_2d: bool = False) -> np.ndarray: + """Get impedance matrices for all lines in three-phase system + + For each line, extract its 3x3 impedance matrix from line_config and + multiply by line length to get total impedance. + + Args: + reshape_2d: If True, reshape output to (n_lines * 3, 3) instead of (n_lines, 3, 3) + + Returns: + numpy array of shape (n_lines, 3, 3) or (n_lines * 3, 3) if reshape_2d=True + Each element is the total impedance matrix (config impedance * length) + + Raises: + AttributeError: If line_config or lines does not exist + + Example: + >>> z_matrices = case.get_line_impedance_matrices() + >>> z_matrices.shape + (113, 3, 3) # For 113 lines + >>> z_matrices_2d = case.get_line_impedance_matrices(reshape_2d=True) + >>> z_matrices_2d.shape + (339, 3) # 113 * 3 rows, 3 columns + """ + if not hasattr(self, 'line_config'): + raise AttributeError( + f"Case {self.name} does not have 'line_config' attribute. " + "This method is only available for three-phase cases." + ) + + if not hasattr(self, 'lines'): + raise AttributeError( + f"Case {self.name} does not have 'lines' attribute." + ) + + # Build impedance matrices using list comprehension + z_matrices = np.array([ + self.get_3ph_matrix(self.line_config.loc[int(line['config_name'])]) * line['length'] + for _, line in self.lines.iterrows() + ]) + + # Optionally reshape to 2D + if reshape_2d: + return z_matrices.reshape(-1, 3) + + return z_matrices + diff --git a/powergrid_case/distribution/Case118zh.py b/powergrid_case/distribution/Case118zh.py new file mode 100644 index 0000000000000000000000000000000000000000..92ed8d1286804be0d2673da9057e82e181e22a47 --- /dev/null +++ b/powergrid_case/distribution/Case118zh.py @@ -0,0 +1,452 @@ +"""Power System Case: 118zh + +Data Source: MATPOWER case file +Base MVA: 10.0 MVA +Base kV: 11.0 kV + +Unit conversions applied: + - Pd/Qd converted from kW/kVar to MW/MVAr (divided by 1000) + - Pd converted from kVA to MW/MVAr (divided by 1000) + - r/x converted from Ohms to p.u. (Z_pu = Z_ohm * Sbase / Vbase^2) + + +Nodes (bus) columns: + id, type, Pd, Qd, Gs, Bs, Vm, Va, baseKV, Vmax, Vmin + - type: 1=PQ, 2=PV, 3=Slack + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - Gs/Bs: Shunt conductance/susceptance (MW/MVAr at V=1.0 p.u.) + - Vm: Voltage magnitude (p.u.) + - Va: Voltage angle (degrees) + - baseKV: Base voltage (kV) + - Vmax/Vmin: Voltage limits (p.u.) + +Units (generators) columns: + id, bus_id, Pg, Qg, Qmax, Qmin, Vg, mBase, status, Pmax, Pmin, mc_a, mc_b, mc_c + - Pg/Qg: Active/Reactive power output (MW/MVAr) + - Qmax/Qmin: Reactive power limits (MVAr) + - Vg: Voltage setpoint (p.u.) + - mBase: Machine base (MVA) + - status: >0 in-service, <=0 out-of-service + - Pmax/Pmin: Active power limits (MW) + - mc_a/mc_b/mc_c: Marginal cost coefficients (quadratic) + +Lines (branches) columns: + id, from, to, r, x, b, rateA, ratio, angle, status, floor, cap + - r/x: Resistance/Reactance (p.u.) + - b: Line charging susceptance (p.u.) + - rateA: Long-term rating (MVA) + - ratio: Transformer tap ratio (0 for line) + - angle: Transformer phase shift (degrees) + - status: 1=in-service, 0=out-of-service + - floor/cap: Power flow limits (MW) + +Loads columns: + id, bus_id, Pd, Qd, mc_a, mc_b, mc_c, d_max, d_min + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - mc_a/mc_b/mc_c: Marginal utility coefficients + - d_max/d_min: Demand limits (MW) +""" +from math import inf + +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case118zh(ClearCase): + GRID_TYPE = "distribution" + BUS_COUNT = 118 + VOLTAGE_LEVEL = "MV" + SOURCE = "MATPOWER" + DESCRIPTION = "118-bus Zhang distribution system" + + def __init__(self, *args, **kwargs): + # System base values + self.baseMVA = 10.0 + self.baseKV = 11.0 + + # Node (bus) data + self.nodes = DataFrame( + ['id', 'type', 'Pd', 'Qd', 'Gs', 'Bs', 'Vm', 'Va', 'baseKV', 'Vmax', 'Vmin'], + [[1.0, 3.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 11.0, 1.0, 1.0], + [2.0, 1.0, 0.13384000000000001, 0.10114, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [3.0, 1.0, 0.016214, 0.011292, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [4.0, 1.0, 0.034315, 0.021845, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [5.0, 1.0, 0.07301600000000001, 0.06360199999999999, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [6.0, 1.0, 0.1442, 0.068604, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [7.0, 1.0, 0.10447, 0.061725, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [8.0, 1.0, 0.028547, 0.011503, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [9.0, 1.0, 0.08756, 0.051073, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [10.0, 1.0, 0.1982, 0.10676999999999999, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [11.0, 1.0, 0.1468, 0.07599500000000001, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [12.0, 1.0, 0.02604, 0.018687000000000002, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [13.0, 1.0, 0.0521, 0.023219999999999998, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [14.0, 1.0, 0.1419, 0.1175, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [15.0, 1.0, 0.02187, 0.02879, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [16.0, 1.0, 0.03337, 0.026449999999999998, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [17.0, 1.0, 0.03243, 0.02523, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [18.0, 1.0, 0.020234000000000002, 0.011906, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [19.0, 1.0, 0.15694, 0.078523, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [20.0, 1.0, 0.5462899999999999, 0.3514, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [21.0, 1.0, 0.18031, 0.16419999999999998, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [22.0, 1.0, 0.093167, 0.054594000000000004, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [23.0, 1.0, 0.08518, 0.03965, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [24.0, 1.0, 0.1681, 0.095178, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [25.0, 1.0, 0.12511, 0.15022, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [26.0, 1.0, 0.016030000000000003, 0.02462, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [27.0, 1.0, 0.02603, 0.02462, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [28.0, 1.0, 0.59456, 0.52262, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [29.0, 1.0, 0.12062, 0.059116999999999996, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [30.0, 1.0, 0.10238, 0.099554, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [31.0, 1.0, 0.5134, 0.3185, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [32.0, 1.0, 0.47525, 0.45614, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [33.0, 1.0, 0.15143, 0.13679, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [34.0, 1.0, 0.20538, 0.083302, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [35.0, 1.0, 0.1316, 0.093082, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [36.0, 1.0, 0.44839999999999997, 0.36979, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [37.0, 1.0, 0.44051999999999997, 0.32164, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [38.0, 1.0, 0.11254, 0.055134, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [39.0, 1.0, 0.053963000000000004, 0.038998, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [40.0, 1.0, 0.39305, 0.3426, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [41.0, 1.0, 0.32674000000000003, 0.27856000000000003, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [42.0, 1.0, 0.53626, 0.24024, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [43.0, 1.0, 0.076247, 0.066562, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [44.0, 1.0, 0.053520000000000005, 0.03976, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [45.0, 1.0, 0.040328, 0.031964, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [46.0, 1.0, 0.039653, 0.020758, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [47.0, 1.0, 0.06619499999999999, 0.042360999999999996, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [48.0, 1.0, 0.073904, 0.051653, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [49.0, 1.0, 0.11477, 0.057965, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [50.0, 1.0, 0.91837, 1.2050999999999998, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [51.0, 1.0, 0.21030000000000001, 0.14665999999999998, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [52.0, 1.0, 0.06668, 0.056608, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [53.0, 1.0, 0.042207, 0.040184, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [54.0, 1.0, 0.43374, 0.28341000000000005, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [55.0, 1.0, 0.0621, 0.02686, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [56.0, 1.0, 0.09246, 0.08838, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [57.0, 1.0, 0.085188, 0.055436, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [58.0, 1.0, 0.3453, 0.3324, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [59.0, 1.0, 0.0225, 0.016829999999999998, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [60.0, 1.0, 0.080551, 0.049156, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [61.0, 1.0, 0.09586, 0.09075799999999999, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [62.0, 1.0, 0.06292, 0.047700000000000006, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [63.0, 1.0, 0.4788, 0.46374, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [64.0, 1.0, 0.12093999999999999, 0.052006000000000004, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [65.0, 1.0, 0.13911, 0.10034, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [66.0, 1.0, 0.39177999999999996, 0.1935, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [67.0, 1.0, 0.027741, 0.026713, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [68.0, 1.0, 0.052814, 0.025257, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [69.0, 1.0, 0.06689, 0.038713000000000004, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [70.0, 1.0, 0.4675, 0.39514, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [71.0, 1.0, 0.59485, 0.23974, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [72.0, 1.0, 0.1325, 0.084363, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [73.0, 1.0, 0.052698999999999996, 0.022482, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [74.0, 1.0, 0.86979, 0.614775, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [75.0, 1.0, 0.031349, 0.029817, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [76.0, 1.0, 0.19238999999999998, 0.12243000000000001, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [77.0, 1.0, 0.06575, 0.04537, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [78.0, 1.0, 0.23815, 0.22322, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [79.0, 1.0, 0.29455000000000003, 0.16247, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [80.0, 1.0, 0.48557, 0.43792000000000003, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [81.0, 1.0, 0.24353, 0.18303, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [82.0, 1.0, 0.24353, 0.18303, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [83.0, 1.0, 0.13425, 0.11929000000000001, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [84.0, 1.0, 0.02271, 0.027960000000000002, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [85.0, 1.0, 0.049513, 0.026515, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [86.0, 1.0, 0.38377999999999995, 0.25716, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [87.0, 1.0, 0.049640000000000004, 0.0206, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [88.0, 1.0, 0.022473, 0.011805999999999999, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [89.0, 1.0, 0.06293, 0.04296, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [90.0, 1.0, 0.030670000000000003, 0.03493, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [91.0, 1.0, 0.06253, 0.06679, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [92.0, 1.0, 0.11456999999999999, 0.081748, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [93.0, 1.0, 0.081292, 0.066526, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [94.0, 1.0, 0.031733, 0.015960000000000002, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [95.0, 1.0, 0.03332, 0.06048, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [96.0, 1.0, 0.53128, 0.22485, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [97.0, 1.0, 0.50703, 0.36742, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [98.0, 1.0, 0.02639, 0.011699999999999999, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [99.0, 1.0, 0.04599, 0.030392, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [100.0, 1.0, 0.10066, 0.047572, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [101.0, 1.0, 0.45648, 0.3503, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [102.0, 1.0, 0.5225599999999999, 0.44929, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [103.0, 1.0, 0.40843, 0.16846, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [104.0, 1.0, 0.14148, 0.13425, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [105.0, 1.0, 0.10443000000000001, 0.066024, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [106.0, 1.0, 0.096793, 0.083647, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [107.0, 1.0, 0.49392, 0.41934, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [108.0, 1.0, 0.22538, 0.13588, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [109.0, 1.0, 0.5092099999999999, 0.38721, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [110.0, 1.0, 0.1885, 0.17346, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [111.0, 1.0, 0.91803, 0.89855, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [112.0, 1.0, 0.30507999999999996, 0.21537, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [113.0, 1.0, 0.054380000000000005, 0.04097, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [114.0, 1.0, 0.21114, 0.19290000000000002, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [115.0, 1.0, 0.067009, 0.053336, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [116.0, 1.0, 0.16207, 0.090321, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [117.0, 1.0, 0.048784999999999995, 0.029155999999999998, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9], + [118.0, 1.0, 0.0339, 0.01898, 0.0, 0.0, 1.0, 0.0, 11.0, 1.1, 0.9]]) + + # Generator (unit) data + self.units = DataFrame( + ['id', 'bus_id', 'Pg', 'Qg', 'Qmax', 'Qmin', 'Vg', 'mBase', 'status', 'Pmax', 'Pmin', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min'], + [[1.0, 1.0, 0.0, 0.0, 10.0, -10.0, 1.0, 100.0, 1.0, 10.0, 0.0, 0.0, 0.0, 20.0, 10.0, 0.0]]) + + # Branch (line) data + self.lines = DataFrame( + ['id', 'from', 'to', 'r', 'x', 'b', 'rateA', 'ratio', 'angle', 'status', 'floor', 'cap'], + [[1.0, 1.0, 2.0, 0.0029752066115702478, 0.0010710743801652892, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [2.0, 2.0, 3.0, 0.0027272727272727275, 0.0009818181818181818, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [3.0, 2.0, 4.0, 0.00371900826446281, 0.0013388429752066115, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [4.0, 4.0, 5.0, 0.0012396694214876034, 0.004462809917355372, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [5.0, 5.0, 6.0, 0.0012396694214876034, 0.004462809917355372, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [6.0, 6.0, 7.0, 0.0012396694214876034, 0.0010330578512396695, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [7.0, 7.0, 8.0, 0.0014876033057851239, 0.0011570247933884298, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [8.0, 8.0, 9.0, 0.0017355371900826448, 0.005206611570247934, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [9.0, 2.0, 10.0, 0.01371900826446281, 0.011107438016528925, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [10.0, 10.0, 11.0, 0.009256198347107438, 0.006520661157024793, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [11.0, 11.0, 12.0, 0.015454545454545455, 0.025867768595041325, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [12.0, 12.0, 13.0, 0.011735537190082643, 0.012495867768595043, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [13.0, 13.0, 14.0, 0.01487603305785124, 0.009752066115702479, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [14.0, 14.0, 15.0, 0.012396694214876033, 0.00371900826446281, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [15.0, 15.0, 16.0, 0.01322314049586777, 0.01487603305785124, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [16.0, 16.0, 17.0, 0.012975206611570249, 0.01413223140495868, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [17.0, 11.0, 18.0, 0.018016528925619835, 0.023553719008264463, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [18.0, 18.0, 19.0, 0.009752066115702479, 0.015289256198347107, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [19.0, 19.0, 20.0, 0.01322314049586777, 0.01619834710743802, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [20.0, 20.0, 21.0, 0.009917355371900827, 0.015619834710743801, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [21.0, 21.0, 22.0, 0.009917355371900827, 0.006520661157024793, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [22.0, 22.0, 23.0, 0.1165289256198347, 0.05975206611570248, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [23.0, 23.0, 24.0, 0.02421487603305785, 0.011140495867768595, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [24.0, 24.0, 25.0, 0.010991735537190083, 0.00859504132231405, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [25.0, 25.0, 26.0, 0.014710743801652892, 0.011074380165289258, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [26.0, 26.0, 27.0, 0.014710743801652892, 0.011074380165289258, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [27.0, 4.0, 28.0, 0.0012396694214876034, 0.0024462809917355373, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [28.0, 28.0, 29.0, 0.0009917355371900827, 0.00228099173553719, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [29.0, 29.0, 30.0, 0.009917355371900827, 0.022859504132231406, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [30.0, 30.0, 31.0, 0.017355371900826446, 0.020082644628099174, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [31.0, 31.0, 32.0, 0.009917355371900827, 0.004462809917355372, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [32.0, 32.0, 33.0, 0.014710743801652892, 0.019338842975206612, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [33.0, 33.0, 34.0, 0.014710743801652892, 0.019338842975206612, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [34.0, 34.0, 35.0, 0.012727272727272728, 0.013388429752066116, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [35.0, 30.0, 36.0, 0.015454545454545455, 0.0215702479338843, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [36.0, 36.0, 37.0, 0.010991735537190083, 0.008181818181818182, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [37.0, 29.0, 38.0, 0.027272727272727275, 0.01603305785123967, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [38.0, 38.0, 39.0, 0.0256198347107438, 0.01603305785123967, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [39.0, 39.0, 40.0, 0.010743801652892562, 0.01603305785123967, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [40.0, 40.0, 41.0, 0.023140495867768597, 0.012396694214876033, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [41.0, 41.0, 42.0, 0.09752066115702479, 0.07024793388429752, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [42.0, 42.0, 43.0, 0.03471074380165289, 0.020132231404958678, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [43.0, 43.0, 44.0, 0.022314049586776862, 0.008033057851239669, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [44.0, 44.0, 45.0, 0.028016528925619837, 0.010090909090909091, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [45.0, 45.0, 46.0, 0.022314049586776862, 0.014702479338842975, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [46.0, 35.0, 47.0, 0.017355371900826446, 0.011429752066115703, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [47.0, 47.0, 48.0, 0.009917355371900827, 0.006520661157024793, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [48.0, 48.0, 49.0, 0.012396694214876033, 0.00815702479338843, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [49.0, 49.0, 50.0, 0.012396694214876033, 0.00815702479338843, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [50.0, 50.0, 51.0, 0.019834710743801654, 0.013066115702479338, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [51.0, 51.0, 52.0, 0.009917355371900827, 0.006520661157024793, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [52.0, 52.0, 53.0, 0.03347107438016529, 0.012049586776859505, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [53.0, 53.0, 54.0, 0.03347107438016529, 0.012049586776859505, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [54.0, 29.0, 55.0, 0.03231404958677686, 0.01165289256198347, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [55.0, 55.0, 56.0, 0.03355371900826447, 0.012074380165289257, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [56.0, 56.0, 57.0, 0.03355371900826447, 0.012074380165289257, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [57.0, 57.0, 58.0, 0.05834710743801653, 0.04513223140495868, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [58.0, 58.0, 59.0, 0.027933884297520663, 0.010066115702479339, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 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0.0, 0.0], + [69.0, 69.0, 70.0, 0.07950413223140496, 0.06289256198347108, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [70.0, 70.0, 71.0, 0.013636363636363637, 0.0049586776859504135, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [71.0, 71.0, 72.0, 0.025041322314049586, 0.009024793388429753, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [72.0, 72.0, 73.0, 0.025041322314049586, 0.009024793388429753, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [73.0, 73.0, 74.0, 0.01702479338842975, 0.011900826446280991, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [74.0, 74.0, 75.0, 0.01925619834710744, 0.006942148760330579, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [75.0, 75.0, 76.0, 0.04884297520661157, 0.014652892561983473, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [76.0, 76.0, 77.0, 0.010413223140495868, 0.0037438016528925622, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [77.0, 64.0, 78.0, 0.046198347107438024, 0.030471074380165292, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [78.0, 78.0, 79.0, 0.015371900826446282, 0.010140495867768596, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [79.0, 79.0, 80.0, 0.015371900826446282, 0.010140495867768596, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [80.0, 80.0, 81.0, 0.021487603305785124, 0.011487603305785125, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [81.0, 81.0, 82.0, 0.012727272727272728, 0.012231404958677685, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [82.0, 82.0, 83.0, 0.01900826446280992, 0.010578512396694216, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [83.0, 83.0, 84.0, 0.020826446280991735, 0.008760330578512396, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [84.0, 84.0, 85.0, 0.01487603305785124, 0.012231404958677685, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [85.0, 79.0, 86.0, 0.01322314049586777, 0.015041322314049586, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [86.0, 86.0, 87.0, 0.01652892561983471, 0.01900826446280992, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [87.0, 87.0, 88.0, 0.01322314049586777, 0.03247933884297521, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [88.0, 65.0, 89.0, 0.05528925619834711, 0.01993388429752066, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [89.0, 89.0, 90.0, 0.021983471074380166, 0.010140495867768596, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [90.0, 90.0, 91.0, 0.021983471074380166, 0.010140495867768596, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [91.0, 91.0, 92.0, 0.021983471074380166, 0.010140495867768596, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [92.0, 92.0, 93.0, 0.021983471074380166, 0.010140495867768596, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [93.0, 93.0, 94.0, 0.01925619834710744, 0.00950413223140496, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [94.0, 94.0, 95.0, 0.040991735537190085, 0.011404958677685952, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [95.0, 91.0, 96.0, 0.01619834710743802, 0.01487603305785124, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [96.0, 96.0, 97.0, 0.01619834710743802, 0.01487603305785124, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [97.0, 97.0, 98.0, 0.015421487603305785, 0.010082644628099173, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [98.0, 98.0, 99.0, 0.006165289256198347, 0.02628099173553719, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [99.0, 1.0, 100.0, 0.005165289256198347, 0.002190082644628099, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [100.0, 100.0, 101.0, 0.012404958677685951, 0.019338842975206612, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [101.0, 101.0, 102.0, 0.011132231404958677, 0.0073388429752066124, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [102.0, 102.0, 103.0, 0.01906611570247934, 0.00994214876033058, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [103.0, 103.0, 104.0, 0.03694214876033058, 0.013289256198347107, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [104.0, 104.0, 105.0, 0.013487603305785125, 0.004859504132231405, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [105.0, 105.0, 106.0, 0.027272727272727275, 0.008181818181818182, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [106.0, 106.0, 107.0, 0.012892561983471074, 0.004636363636363636, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [107.0, 107.0, 108.0, 0.03156198347107438, 0.011355371900826446, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [108.0, 108.0, 109.0, 0.013438016528925619, 0.004834710743801653, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [109.0, 109.0, 110.0, 0.03156198347107438, 0.011355371900826446, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [110.0, 110.0, 111.0, 0.020206611570247935, 0.0072644628099173564, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [111.0, 110.0, 112.0, 0.01725619834710744, 0.006223140495867769, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [112.0, 112.0, 113.0, 0.019016528925619836, 0.00684297520661157, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [113.0, 100.0, 114.0, 0.050429752066115704, 0.018148760330578512, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [114.0, 114.0, 115.0, 0.015421487603305785, 0.010495867768595043, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [115.0, 115.0, 116.0, 0.03084297520661157, 0.020330578512396693, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [116.0, 116.0, 117.0, 0.03347107438016529, 0.030330578512396695, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [117.0, 117.0, 118.0, 0.04041322314049587, 0.036198347107438016, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [118.0, 46.0, 27.0, 0.04345454545454546, 0.024173553719008263, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [119.0, 17.0, 27.0, 0.04345454545454546, 0.02409917355371901, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [120.0, 8.0, 24.0, 0.03530578512396695, 0.012719008264462811, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [121.0, 54.0, 43.0, 0.03966942148760331, 0.014280991735537192, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [122.0, 62.0, 49.0, 0.02975206611570248, 0.010710743801652892, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [123.0, 37.0, 62.0, 0.047107438016528926, 0.04727272727272727, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [124.0, 9.0, 40.0, 0.043801652892561986, 0.027669421487603305, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [125.0, 58.0, 96.0, 0.032702479338842974, 0.011776859504132231, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [126.0, 73.0, 91.0, 0.05619834710743802, 0.053553719008264465, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [127.0, 88.0, 75.0, 0.0335702479338843, 0.01209917355371901, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [128.0, 99.0, 77.0, 0.03823140495867769, 0.013834710743801652, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [129.0, 108.0, 83.0, 0.05380165289256199, 0.019338842975206612, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [130.0, 105.0, 86.0, 0.06714876033057851, 0.024173553719008263, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [131.0, 110.0, 118.0, 0.058586776859504135, 0.02109917355371901, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [132.0, 25.0, 35.0, 0.04132231404958678, 0.04132231404958678, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]) + + # Load data + self.loads = DataFrame( + ['id', 'bus_id', 'Pd', 'Qd', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2.0, 2.0, 0.13384000000000001, 0.10114, 0.0, 0.0, 0.0, 0.13384000000000001, 0.13384000000000001], + [3.0, 3.0, 0.016214, 0.011292, 0.0, 0.0, 0.0, 0.016214, 0.016214], + [4.0, 4.0, 0.034315, 0.021845, 0.0, 0.0, 0.0, 0.034315, 0.034315], + [5.0, 5.0, 0.07301600000000001, 0.06360199999999999, 0.0, 0.0, 0.0, 0.07301600000000001, 0.07301600000000001], + [6.0, 6.0, 0.1442, 0.068604, 0.0, 0.0, 0.0, 0.1442, 0.1442], + [7.0, 7.0, 0.10447, 0.061725, 0.0, 0.0, 0.0, 0.10447, 0.10447], + [8.0, 8.0, 0.028547, 0.011503, 0.0, 0.0, 0.0, 0.028547, 0.028547], + [9.0, 9.0, 0.08756, 0.051073, 0.0, 0.0, 0.0, 0.08756, 0.08756], + [10.0, 10.0, 0.1982, 0.10676999999999999, 0.0, 0.0, 0.0, 0.1982, 0.1982], + [11.0, 11.0, 0.1468, 0.07599500000000001, 0.0, 0.0, 0.0, 0.1468, 0.1468], + [12.0, 12.0, 0.02604, 0.018687000000000002, 0.0, 0.0, 0.0, 0.02604, 0.02604], + [13.0, 13.0, 0.0521, 0.023219999999999998, 0.0, 0.0, 0.0, 0.0521, 0.0521], + [14.0, 14.0, 0.1419, 0.1175, 0.0, 0.0, 0.0, 0.1419, 0.1419], + [15.0, 15.0, 0.02187, 0.02879, 0.0, 0.0, 0.0, 0.02187, 0.02187], + [16.0, 16.0, 0.03337, 0.026449999999999998, 0.0, 0.0, 0.0, 0.03337, 0.03337], + [17.0, 17.0, 0.03243, 0.02523, 0.0, 0.0, 0.0, 0.03243, 0.03243], + [18.0, 18.0, 0.020234000000000002, 0.011906, 0.0, 0.0, 0.0, 0.020234000000000002, 0.020234000000000002], + [19.0, 19.0, 0.15694, 0.078523, 0.0, 0.0, 0.0, 0.15694, 0.15694], + [20.0, 20.0, 0.5462899999999999, 0.3514, 0.0, 0.0, 0.0, 0.5462899999999999, 0.5462899999999999], + [21.0, 21.0, 0.18031, 0.16419999999999998, 0.0, 0.0, 0.0, 0.18031, 0.18031], + [22.0, 22.0, 0.093167, 0.054594000000000004, 0.0, 0.0, 0.0, 0.093167, 0.093167], + [23.0, 23.0, 0.08518, 0.03965, 0.0, 0.0, 0.0, 0.08518, 0.08518], + [24.0, 24.0, 0.1681, 0.095178, 0.0, 0.0, 0.0, 0.1681, 0.1681], + [25.0, 25.0, 0.12511, 0.15022, 0.0, 0.0, 0.0, 0.12511, 0.12511], + [26.0, 26.0, 0.016030000000000003, 0.02462, 0.0, 0.0, 0.0, 0.016030000000000003, 0.016030000000000003], + [27.0, 27.0, 0.02603, 0.02462, 0.0, 0.0, 0.0, 0.02603, 0.02603], + [28.0, 28.0, 0.59456, 0.52262, 0.0, 0.0, 0.0, 0.59456, 0.59456], + [29.0, 29.0, 0.12062, 0.059116999999999996, 0.0, 0.0, 0.0, 0.12062, 0.12062], + [30.0, 30.0, 0.10238, 0.099554, 0.0, 0.0, 0.0, 0.10238, 0.10238], + [31.0, 31.0, 0.5134, 0.3185, 0.0, 0.0, 0.0, 0.5134, 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+ [94.0, 94.0, 0.031733, 0.015960000000000002, 0.0, 0.0, 0.0, 0.031733, 0.031733], + [95.0, 95.0, 0.03332, 0.06048, 0.0, 0.0, 0.0, 0.03332, 0.03332], + [96.0, 96.0, 0.53128, 0.22485, 0.0, 0.0, 0.0, 0.53128, 0.53128], + [97.0, 97.0, 0.50703, 0.36742, 0.0, 0.0, 0.0, 0.50703, 0.50703], + [98.0, 98.0, 0.02639, 0.011699999999999999, 0.0, 0.0, 0.0, 0.02639, 0.02639], + [99.0, 99.0, 0.04599, 0.030392, 0.0, 0.0, 0.0, 0.04599, 0.04599], + [100.0, 100.0, 0.10066, 0.047572, 0.0, 0.0, 0.0, 0.10066, 0.10066], + [101.0, 101.0, 0.45648, 0.3503, 0.0, 0.0, 0.0, 0.45648, 0.45648], + [102.0, 102.0, 0.5225599999999999, 0.44929, 0.0, 0.0, 0.0, 0.5225599999999999, 0.5225599999999999], + [103.0, 103.0, 0.40843, 0.16846, 0.0, 0.0, 0.0, 0.40843, 0.40843], + [104.0, 104.0, 0.14148, 0.13425, 0.0, 0.0, 0.0, 0.14148, 0.14148], + [105.0, 105.0, 0.10443000000000001, 0.066024, 0.0, 0.0, 0.0, 0.10443000000000001, 0.10443000000000001], + [106.0, 106.0, 0.096793, 0.083647, 0.0, 0.0, 0.0, 0.096793, 0.096793], + [107.0, 107.0, 0.49392, 0.41934, 0.0, 0.0, 0.0, 0.49392, 0.49392], + [108.0, 108.0, 0.22538, 0.13588, 0.0, 0.0, 0.0, 0.22538, 0.22538], + [109.0, 109.0, 0.5092099999999999, 0.38721, 0.0, 0.0, 0.0, 0.5092099999999999, 0.5092099999999999], + [110.0, 110.0, 0.1885, 0.17346, 0.0, 0.0, 0.0, 0.1885, 0.1885], + [111.0, 111.0, 0.91803, 0.89855, 0.0, 0.0, 0.0, 0.91803, 0.91803], + [112.0, 112.0, 0.30507999999999996, 0.21537, 0.0, 0.0, 0.0, 0.30507999999999996, 0.30507999999999996], + [113.0, 113.0, 0.054380000000000005, 0.04097, 0.0, 0.0, 0.0, 0.054380000000000005, 0.054380000000000005], + [114.0, 114.0, 0.21114, 0.19290000000000002, 0.0, 0.0, 0.0, 0.21114, 0.21114], + [115.0, 115.0, 0.067009, 0.053336, 0.0, 0.0, 0.0, 0.067009, 0.067009], + [116.0, 116.0, 0.16207, 0.090321, 0.0, 0.0, 0.0, 0.16207, 0.16207], + [117.0, 117.0, 0.048784999999999995, 0.029155999999999998, 0.0, 0.0, 0.0, 0.048784999999999995, 0.048784999999999995], + [118.0, 118.0, 0.0339, 0.01898, 0.0, 0.0, 0.0, 0.0339, 0.0339]]) + + self.real_params = True + super().__init__(*args, **kwargs) diff --git a/powergrid_case/distribution/Case123.py b/powergrid_case/distribution/Case123.py new file mode 100644 index 0000000000000000000000000000000000000000..320ea71ab0afa4828080105f8b1fd5b67060c38c --- /dev/null +++ b/powergrid_case/distribution/Case123.py @@ -0,0 +1,458 @@ +from powerzoo.case.CaseBase import ClearCase, DataFrame + +class Case123(ClearCase): + GRID_TYPE = "distribution" + BUS_COUNT = 123 + PHASE = "3" + VOLTAGE_LEVEL = "MV" + SOURCE = "MATPOWER" + DESCRIPTION = "IEEE 123-bus three-phase distribution" + + def __init__(self, *args, **kwargs): + # System base values + self.baseMVA = 10 + self.baseKV = 4.16 + + # Node (bus) data + self.nodes = DataFrame( + ['id', 'type', 'Pd_A', 'Qd_A', 'Pd_B', 'Qd_B', 'Pd_C', 'Qd_C', 'Gs', 'Bs', 'Vm', 'Va', 'baseKV', 'Vmax', 'Vmin'], + [[1, 3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.0, 1.0], + [2, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [3, 1, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [4, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [5, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [6, 1, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [7, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [8, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [9, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [10, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [11, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [12, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [13, 1, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [14, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [15, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [16, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [17, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [18, 1, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [19, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [20, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [21, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [22, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [23, 1, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [24, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [25, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [26, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [27, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [28, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [29, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [30, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [31, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [32, 1, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [33, 1, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [34, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [35, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [36, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [37, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [38, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [39, 1, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [40, 1, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [41, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [42, 1, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [43, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [44, 1, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [45, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [46, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [47, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [48, 1, 0.0035, 0.0025, 0.0035, 0.0025, 0.0035, 0.0025, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [49, 1, 0.007, 0.005, 0.007, 0.005, 0.007, 0.005, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [50, 1, 0.0035, 0.0025, 0.007, 0.005, 0.0035, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [51, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [52, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [53, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [54, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [55, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [56, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [57, 1, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [58, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [59, 1, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [60, 1, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [61, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [62, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [63, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [64, 1, 0.0, 0.0, 0.0075, 0.0035, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [65, 1, 0.0035, 0.0025, 0.0035, 0.0025, 0.007, 0.005, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [66, 1, 0.0, 0.0, 0.0, 0.0, 0.0075, 0.0035, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [67, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [68, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [69, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [70, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [71, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [72, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [73, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [74, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [75, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [76, 1, 0.0105, 0.008, 0.007, 0.005, 0.007, 0.005, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [77, 1, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [78, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [79, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [80, 1, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [81, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [82, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [83, 1, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [84, 1, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [85, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [86, 1, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [87, 1, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [88, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [89, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [90, 1, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [91, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [92, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [93, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [94, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [95, 1, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [96, 1, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [97, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [98, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [99, 1, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [100, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [101, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [102, 1, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [103, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [104, 1, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [105, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [106, 1, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [107, 1, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [108, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [109, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [110, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [111, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [112, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [113, 1, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8], + [114, 1, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 4.16, 1.2, 0.8]]) + + # Generator (unit) data + self.units = DataFrame( + ['id', 'bus_id', 'Pg', 'Qg', 'Qmax', 'Qmin', 'Vg', 'mBase', 'status', 'Pmax', 'Pmin', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min'], + [[1, 114, 0.0, 0.0, 200.0, -200.0, 1.0, 1.0, 1, 200.0, -200.0, 0.0, 0.0, 0.0, 200.0, -200.0]]) + + # Line (branch) data + self.lines = DataFrame( + ['id', 'from', 'to', 'config_name', 'length', 'type', 'rateA', 'ratio', 'angle', 'status', 'floor', 'cap'], + [[1, 1, 2, 1, 0.075758, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [2, 2, 3, 10, 0.033144, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [3, 2, 4, 11, 0.047348, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [4, 4, 5, 11, 0.037879, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [5, 4, 6, 11, 0.061553, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [6, 6, 7, 11, 0.047348, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [7, 2, 8, 1, 0.056818, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [8, 8, 9, 1, 0.037879, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [9, 9, 10, 9, 0.042614, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [10, 15, 11, 9, 0.047348, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [11, 15, 12, 9, 0.047348, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [12, 9, 13, 10, 0.042614, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [13, 9, 14, 1, 0.056818, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [14, 10, 15, 9, 0.080492, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [15, 35, 16, 11, 0.018939, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [16, 16, 17, 11, 0.071023, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [17, 16, 18, 11, 0.066288, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [18, 14, 19, 2, 0.15625, 'CABN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [19, 19, 20, 9, 0.047348, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [20, 20, 21, 9, 0.061553, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [21, 19, 22, 2, 0.056818, 'CABN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [22, 22, 23, 10, 0.099432, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [23, 22, 24, 2, 0.047348, 'CABN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [24, 24, 25, 11, 0.104167, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [25, 24, 26, 2, 0.052083, 'CABN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [26, 26, 27, 7, 0.066288, 'ACN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [27, 27, 28, 7, 0.052083, 'ACN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [28, 26, 29, 2, 0.037879, 'CABN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [29, 29, 30, 2, 0.056818, 'CABN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [30, 30, 31, 2, 0.066288, 'CABN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [31, 27, 32, 11, 0.042614, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [32, 32, 33, 11, 0.056818, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [33, 28, 34, 9, 0.094697, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [34, 14, 35, 11, 0.028409, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [35, 19, 36, 4, 0.071023, 'CBAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [36, 36, 37, 8, 0.123106, 'ABN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [37, 37, 38, 9, 0.056818, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [38, 37, 39, 10, 0.047348, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [39, 39, 40, 10, 0.061553, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [40, 36, 41, 1, 0.047348, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [41, 41, 42, 11, 0.061553, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [42, 41, 43, 1, 0.047348, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [43, 43, 44, 10, 0.094697, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [44, 43, 45, 1, 0.037879, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [45, 45, 46, 9, 0.037879, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [46, 46, 47, 9, 0.056818, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [47, 45, 48, 1, 0.047348, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [48, 48, 49, 4, 0.028409, 'CBAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [49, 48, 50, 4, 0.047348, 'CBAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [50, 50, 51, 4, 0.047348, 'CBAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [51, 51, 52, 4, 0.047348, 'CBAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [52, 14, 53, 1, 0.075758, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [53, 53, 54, 1, 0.037879, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [54, 54, 55, 1, 0.023674, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [55, 55, 56, 1, 0.052083, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [56, 56, 57, 1, 0.052083, 'ABCN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [57, 55, 58, 3, 0.066288, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [58, 58, 59, 10, 0.047348, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [59, 59, 60, 10, 0.047348, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [60, 58, 61, 3, 0.142045, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [61, 61, 62, 12, 0.047348, 'nan', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [62, 62, 63, 12, 0.033144, 'nan', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [63, 63, 64, 12, 0.066288, 'nan', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [64, 64, 65, 12, 0.080492, 'nan', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [65, 65, 66, 12, 0.061553, 'nan', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [66, 61, 67, 6, 0.066288, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [67, 67, 68, 9, 0.037879, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [68, 68, 69, 9, 0.052083, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [69, 69, 70, 9, 0.061553, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [70, 70, 71, 9, 0.052083, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [71, 67, 72, 3, 0.052083, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [72, 72, 73, 11, 0.052083, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [73, 73, 74, 11, 0.066288, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [74, 74, 75, 11, 0.075758, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [75, 72, 76, 3, 0.037879, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [76, 76, 77, 6, 0.075758, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [77, 77, 78, 6, 0.018939, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [78, 78, 79, 6, 0.042614, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [79, 78, 80, 6, 0.089962, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [80, 80, 81, 6, 0.089962, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [81, 81, 82, 6, 0.047348, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [82, 82, 83, 6, 0.047348, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [83, 81, 84, 11, 0.127841, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [84, 84, 85, 11, 0.089962, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [85, 76, 86, 3, 0.132576, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [86, 86, 87, 6, 0.085227, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [87, 87, 88, 9, 0.033144, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [88, 87, 89, 6, 0.052083, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [89, 89, 90, 10, 0.042614, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [90, 89, 91, 6, 0.042614, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [91, 91, 92, 11, 0.056818, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [92, 91, 93, 6, 0.042614, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [93, 93, 94, 9, 0.052083, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [94, 93, 95, 6, 0.056818, 'ACBN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [95, 95, 96, 10, 0.037879, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [96, 67, 97, 3, 0.047348, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [97, 97, 98, 3, 0.052083, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [98, 98, 99, 3, 0.104167, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [99, 99, 100, 3, 0.056818, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [100, 97, 101, 3, 0.047348, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [101, 101, 102, 11, 0.042614, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [102, 102, 103, 11, 0.061553, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [103, 103, 104, 11, 0.132576, 'CN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [104, 101, 105, 3, 0.052083, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [105, 105, 106, 10, 0.042614, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [106, 106, 107, 10, 0.108902, 'BN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [107, 105, 108, 3, 0.061553, 'BCAN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [108, 108, 109, 9, 0.085227, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [109, 109, 110, 9, 0.056818, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [110, 110, 111, 9, 0.108902, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [111, 110, 112, 9, 0.023674, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [112, 112, 113, 9, 0.099432, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [113, 113, 114, 9, 0.061553, 'AN', 0.0, 0.0, 0.0, 1.0, 0.0, 0.0]]) + + # Line configuration data (Z in ohms per mile, B in micro Siemens per mile) + self.line_config = DataFrame( + ['id', 'Z11', 'Z12', 'Z13', 'Z21', 'Z22', 'Z23', 'Z31', 'Z32', 'Z33', 'B11', 'B12', 'B13', 'B21', 'B22', 'B23', 'B31', 'B32', 'B33'], + [[1, (0.4576+1.078j), (0.156+0.5017j), (0.1535+0.3849j), (0.156+0.5017j), (0.4666+1.0482j), (0.158+0.4236j), (0.1535+0.3849j), (0.158+0.4236j), (0.4615+1.0651j), 5.6765, -1.8319, -0.6982, -1.8319, 5.9809, -1.1645, -0.6982, -1.1645, 5.3971], + [2, (0.4666+1.0482j), (0.158+0.4236j), (0.156+0.5017j), (0.158+0.4236j), (0.4615+1.0651j), (0.1535+0.3849j), (0.156+0.5017j), (0.1535+0.3849j), (0.4576+1.078j), 5.9809, -1.1645, -1.8319, -1.1645, 5.3971, -0.6982, -1.8319, -0.6982, 5.6765], + [3, (0.4615+1.0651j), (0.1535+0.3849j), (0.158+0.4236j), (0.1535+0.3849j), (0.4576+1.078j), (0.156+0.5017j), (0.158+0.4236j), (0.156+0.5017j), (0.4666+1.0482j), 5.3971, -0.6982, -1.1645, -0.6982, 5.6765, -1.8319, -1.1645, -1.8319, 5.9809], + [4, (0.4615+1.0651j), (0.158+0.4236j), (0.1535+0.3849j), (0.158+0.4236j), (0.4666+1.0482j), (0.156+0.5017j), (0.1535+0.3849j), (0.156+0.5017j), (0.4576+1.078j), 5.3971, -1.1645, -0.6982, -1.1645, 5.9809, -1.8319, -0.6982, -1.8319, 5.6765], + [5, (0.4666+1.0482j), (0.156+0.5017j), (0.158+0.4236j), (0.156+0.5017j), (0.4576+1.078j), (0.1535+0.3849j), (0.158+0.4236j), (0.1535+0.3849j), (0.4615+1.0651j), 5.9809, -1.8319, -1.1645, -1.8319, 5.6765, -0.6982, -1.1645, -0.6982, 5.3971], + [6, (0.4576+1.078j), (0.1535+0.3849j), (0.156+0.5017j), (0.1535+0.3849j), (0.4615+1.0651j), (0.158+0.4236j), (0.156+0.5017j), (0.158+0.4236j), (0.4666+1.0482j), 5.6765, -0.6982, -1.8319, -0.6982, 5.3971, -1.1645, -1.8319, -1.1645, 5.9809], + [7, (0.4576+1.078j), 0j, (0.1535+0.3849j), 0j, 0j, 0j, (0.1535+0.3849j), 0j, (0.4615+1.0651j), 5.1154, 0.0, -1.0549, 0.0, 0.0, 0.0, -1.0549, 0.0, 5.1704], + [8, (0.4576+1.078j), (0.1535+0.3849j), 0j, (0.1535+0.3849j), (0.4615+1.0651j), 0j, 0j, 0j, 0j, 5.1154, -1.0549, 0.0, -1.0549, 5.1704, 0.0, 0.0, 0.0, 0.0], + [9, (1.3292+1.3475j), 0j, 0j, 0j, 0j, 0j, 0j, 0j, 0j, 4.5193, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [10, 0j, 0j, 0j, 0j, (1.3292+1.3475j), 0j, 0j, 0j, 0j, 0.0, 0.0, 0.0, 0.0, 4.5193, 0.0, 0.0, 0.0, 0.0], + [11, 0j, 0j, 0j, 0j, 0j, 0j, 0j, 0j, (1.3292+1.3475j), 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 4.5193], + [12, (1.5209+0.7521j), (0.5198+0.2775j), (0.4924+0.2157j), (0.5198+0.2775j), (1.5329+0.7162j), (0.5198+0.2775j), (0.4924+0.2157j), (0.5198+0.2775j), (1.5209+0.7521j), 67.2242, 0.0, 0.0, 0.0, 67.2242, 0.0, 0.0, 0.0, 67.2242]]) + + # Load data + self.loads = DataFrame( + ['id', 'bus_id', 'Pd_A', 'Qd_A', 'Pd_B', 'Qd_B', 'Pd_C', 'Qd_C', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2, 2, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [3, 3, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [4, 4, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [5, 5, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [6, 6, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.002, 0.002], + [7, 7, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [8, 8, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [9, 9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [10, 10, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [11, 11, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [12, 12, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [13, 13, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [14, 14, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [15, 15, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [16, 16, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [17, 17, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [18, 18, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.002, 0.002], + [19, 19, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [20, 20, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [21, 21, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [22, 22, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [23, 23, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [24, 24, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [25, 25, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [26, 26, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [27, 27, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [28, 28, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [29, 29, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [30, 30, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [31, 31, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [32, 32, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.002, 0.002], + [33, 33, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.002, 0.002], + [34, 34, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [35, 35, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [36, 36, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [37, 37, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [38, 38, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [39, 39, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [40, 40, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [41, 41, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [42, 42, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.002, 0.002], + [43, 43, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [44, 44, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [45, 45, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [46, 46, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [47, 47, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [48, 48, 0.0035, 0.0025, 0.0035, 0.0025, 0.0035, 0.0025, 0.0, 0.0, 0.0, 0.0105, 0.0105], + [49, 49, 0.007, 0.005, 0.007, 0.005, 0.007, 0.005, 0.0, 0.0, 0.0, 0.021, 0.021], + [50, 50, 0.0035, 0.0025, 0.007, 0.005, 0.0035, 0.002, 0.0, 0.0, 0.0, 0.014, 0.014], + [51, 51, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [52, 52, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [53, 53, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [54, 54, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [55, 55, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [56, 56, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [57, 57, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [58, 58, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [59, 59, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [60, 60, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [61, 61, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [62, 62, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [63, 63, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [64, 64, 0.0, 0.0, 0.0075, 0.0035, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0075, 0.0075], + [65, 65, 0.0035, 0.0025, 0.0035, 0.0025, 0.007, 0.005, 0.0, 0.0, 0.0, 0.014, 0.014], + [66, 66, 0.0, 0.0, 0.0, 0.0, 0.0075, 0.0035, 0.0, 0.0, 0.0, 0.0075, 0.0075], + [67, 67, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [68, 68, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [69, 69, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [70, 70, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [71, 71, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [72, 72, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [73, 73, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [74, 74, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [75, 75, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [76, 76, 0.0105, 0.008, 0.007, 0.005, 0.007, 0.005, 0.0, 0.0, 0.0, 0.0245, 0.0245], + [77, 77, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [78, 78, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [79, 79, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [80, 80, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [81, 81, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [82, 82, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [83, 83, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.002, 0.002], + [84, 84, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.002, 0.002], + [85, 85, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [86, 86, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [87, 87, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [88, 88, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [89, 89, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [90, 90, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [91, 91, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [92, 92, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [93, 93, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [94, 94, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [95, 95, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [96, 96, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [97, 97, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [98, 98, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [99, 99, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [100, 100, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [101, 101, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [102, 102, 0.0, 0.0, 0.0, 0.0, 0.002, 0.001, 0.0, 0.0, 0.0, 0.002, 0.002], + [103, 103, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [104, 104, 0.0, 0.0, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.004, 0.004], + [105, 105, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [106, 106, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [107, 107, 0.0, 0.0, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [108, 108, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [109, 109, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [110, 110, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [111, 111, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [112, 112, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002], + [113, 113, 0.004, 0.002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.004, 0.004], + [114, 114, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.002, 0.002]]) + + self.real_params = True + super().__init__(*args, **kwargs) + +if __name__ == '__main__': + print("=" * 60) + print("Testing IEEE 123-bus System - Graph Connectivity") + print("=" * 60) + + # Create case instance + case = Casegrid_IEEE123() + + # Basic information + print(f"\nSystem Information:") + print(f" Base MVA: {case.baseMVA}") + print(f" Base KV: {case.baseKV}") + print(f" Number of nodes: {len(case.nodes)}") + print(f" Number of lines: {len(case.lines)}") + print(f" Number of units: {len(case.units)}") + print(f" Number of loads: {len(case.loads)}") + print(f" Number of line configs: {len(case.line_config)}") + + # Test graph connectivity + print(f"\n{'=' * 60}") + print("Graph Connectivity Analysis") + print("=" * 60) + + is_connected = case.is_connected_graph() + print(f"\nIs the graph connected? {'✓ YES' if is_connected else '✗ NO'}") + + # Get connected components + components = case.get_graph_components() + print(f"\nNumber of connected components: {len(components)}") + + if len(components) == 1: + print(f" ✓ All {len(case.nodes)} nodes form a single connected component") + else: + print(f" ✗ The graph is disconnected with {len(components)} separate components:") + for i, component in enumerate(components): + print(f" Component {i+1}: {len(component)} nodes") + if len(component) <= 10: + print(f" Nodes: {sorted(component)}") + else: + print(f" Nodes: {sorted(component[:5])} ... {sorted(component[-5:])}") + + # Additional statistics + print(f"\n{'=' * 60}") + print("Network Statistics") + print("=" * 60) + + active_lines = case.lines[case.lines['status'] == 1] + print(f"\nActive lines: {len(active_lines)} / {len(case.lines)}") + + # Count lines per configuration + print(f"\nLines per configuration:") + config_counts = case.lines.groupby('config_name').size().sort_index() + for config_id, count in config_counts.items(): + config_name = int(config_id) + print(f" Config {config_name:2d}: {count:3d} lines") + + # Load statistics + total_pd = case.loads['Pd'].sum() + total_qd = case.loads['Qd'].sum() + print(f"\nTotal system load:") + print(f" Active power (P): {total_pd:.4f} p.u. ({total_pd * case.baseMVA:.2f} MW)") + print(f" Reactive power (Q): {total_qd:.4f} p.u. ({total_qd * case.baseMVA:.2f} MVar)") + + print(f"\n{'=' * 60}") + print("Test completed successfully!") + print("=" * 60) diff --git a/powergrid_case/distribution/Case141.py b/powergrid_case/distribution/Case141.py new file mode 100644 index 0000000000000000000000000000000000000000..9ddc186f0671658ad65162c86c33c9a9201faa6b --- /dev/null +++ b/powergrid_case/distribution/Case141.py @@ -0,0 +1,505 @@ +"""Power System Case: 141 + +Data Source: MATPOWER case file +Base MVA: 10.0 MVA +Base kV: 12.47 kV + +Unit conversions applied: + - Pd converted from kVA to MW/MVAr (divided by 1000, power factor=0.85) + - r/x converted from Ohms to p.u. (Z_pu = Z_ohm * Sbase / Vbase^2) + + +Nodes (bus) columns: + id, type, Pd, Qd, Gs, Bs, Vm, Va, baseKV, Vmax, Vmin + - type: 1=PQ, 2=PV, 3=Slack + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - Gs/Bs: Shunt conductance/susceptance (MW/MVAr at V=1.0 p.u.) + - Vm: Voltage magnitude (p.u.) + - Va: Voltage angle (degrees) + - baseKV: Base voltage (kV) + - Vmax/Vmin: Voltage limits (p.u.) + +Units (generators) columns: + id, bus_id, Pg, Qg, Qmax, Qmin, Vg, mBase, status, Pmax, Pmin, mc_a, mc_b, mc_c + - Pg/Qg: Active/Reactive power output (MW/MVAr) + - Qmax/Qmin: Reactive power limits (MVAr) + - Vg: Voltage setpoint (p.u.) + - mBase: Machine base (MVA) + - status: >0 in-service, <=0 out-of-service + - Pmax/Pmin: Active power limits (MW) + - mc_a/mc_b/mc_c: Marginal cost coefficients (quadratic) + +Lines (branches) columns: + id, from, to, r, x, b, rateA, ratio, angle, status, floor, cap + - r/x: Resistance/Reactance (p.u.) + - b: Line charging susceptance (p.u.) + - rateA: Long-term rating (MVA) + - ratio: Transformer tap ratio (0 for line) + - angle: Transformer phase shift (degrees) + - status: 1=in-service, 0=out-of-service + - floor/cap: Power flow limits (MW) + +Loads columns: + id, bus_id, Pd, Qd, mc_a, mc_b, mc_c, d_max, d_min + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - mc_a/mc_b/mc_c: Marginal utility coefficients + - d_max/d_min: Demand limits (MW) +""" +from math import inf + +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case141(ClearCase): + GRID_TYPE = "distribution" + BUS_COUNT = 141 + VOLTAGE_LEVEL = "MV" + SOURCE = "MATPOWER" + DESCRIPTION = "141-bus Caracas distribution system (Khodr et al., EPSR 2008)" + + def __init__(self, *args, **kwargs): + # System base values + self.baseMVA = 10.0 + self.baseKV = 12.47 + + # Node (bus) data + self.nodes = DataFrame( + ['id', 'type', 'Pd', 'Qd', 'Gs', 'Bs', 'Vm', 'Va', 'baseKV', 'Vmax', 'Vmin'], + [[1.0, 3.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.0, 1.0], + [2.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [3.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [4.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [5.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [6.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [7.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [8.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [9.0, 1.0, 0.0085, 0.00526782687642637, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [10.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [11.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [12.0, 1.0, 0.02125, 0.013169567191065924, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [13.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [14.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [15.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [16.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [17.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [18.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [19.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [20.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [21.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [22.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [23.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [24.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [25.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [26.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [27.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [28.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [29.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [30.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [31.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [32.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [33.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [34.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [35.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [36.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [37.0, 1.0, 0.0425, 0.026339134382131847, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [38.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [39.0, 1.0, 0.017, 0.01053565375285274, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [40.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [41.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [42.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [43.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [44.0, 1.0, 0.0425, 0.026339134382131847, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [45.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [46.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [47.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [48.0, 1.0, 0.10625, 0.06584783595532961, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [49.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [50.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [51.0, 1.0, 0.10625, 0.06584783595532961, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [52.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [53.0, 1.0, 0.085, 0.052678268764263694, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [54.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [55.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [56.0, 1.0, 0.02125, 0.013169567191065924, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [57.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [58.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [59.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [60.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [61.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [62.0, 1.0, 0.17, 0.10535653752852739, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [63.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [64.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [65.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [66.0, 1.0, 0.19125, 0.11852610471959331, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [67.0, 1.0, 0.0425, 0.026339134382131847, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [68.0, 1.0, 0.085, 0.052678268764263694, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [69.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [70.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [71.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [72.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [73.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [74.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [75.0, 1.0, 0.03825, 0.02370522094391866, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [76.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [77.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [78.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [79.0, 1.0, 0.4271249999999999, 0.26470830054042505, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [80.0, 1.0, 0.6375, 0.3950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [81.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [82.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [83.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [84.0, 1.0, 0.19125, 0.11852610471959331, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [85.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [86.0, 1.0, 0.425, 0.26339134382131846, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [87.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [88.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [89.0, 1.0, 0.05525, 0.0342408746967714, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [90.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [91.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [92.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [93.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [94.0, 1.0, 0.0935, 0.05794609564069006, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [95.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [96.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [97.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [98.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [99.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [100.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [101.0, 1.0, 0.01275, 0.007901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [102.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [103.0, 1.0, 0.10625, 0.06584783595532961, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [104.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [105.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [106.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [107.0, 1.0, 0.4271249999999999, 0.26470830054042505, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [108.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [109.0, 1.0, 0.6375, 0.3950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [110.0, 1.0, 0.6375, 0.3950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [111.0, 1.0, 0.02125, 0.013169567191065924, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [112.0, 1.0, 0.425, 0.26339134382131846, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [113.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [114.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [115.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [116.0, 1.0, 0.255, 0.15803480629279107, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [117.0, 1.0, 0.05525, 0.0342408746967714, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [118.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [119.0, 1.0, 0.0935, 0.05794609564069006, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [120.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [121.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [122.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [123.0, 1.0, 0.085, 0.052678268764263694, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [124.0, 1.0, 0.10625, 0.06584783595532961, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [125.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [126.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [127.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [128.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [129.0, 1.0, 0.0935, 0.05794609564069006, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [130.0, 1.0, 0.095625, 0.059263052359796654, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [131.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [132.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [133.0, 1.0, 0.03825, 0.02370522094391866, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [134.0, 1.0, 0.029750000000000002, 0.018437394067492292, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [135.0, 1.0, 0.02125, 0.013169567191065924, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [136.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [137.0, 1.0, 0.04675, 0.02897304782034503, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [138.0, 1.0, 0.0425, 0.026339134382131847, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [139.0, 1.0, 0.0425, 0.026339134382131847, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [140.0, 1.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9], + [141.0, 1.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 1.0, 0.0, 12.47, 1.1, 0.9]]) + + # Generator (unit) data + self.units = DataFrame( + ['id', 'bus_id', 'Pg', 'Qg', 'Qmax', 'Qmin', 'Vg', 'mBase', 'status', 'Pmax', 'Pmin', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min'], + [[1.0, 1.0, 0.0, 0.0, 100.0, -100.0, 1.0, 100.0, 1.0, 100.0, 0.0, 0.0, 0.0, 20.0, 100.0, 0.0]]) + + # Branch (line) data + self.lines = DataFrame( + ['id', 'from', 'to', 'r', 'x', 'b', 'rateA', 'ratio', 'angle', 'status', 'floor', 'cap'], + [[1.0, 1.0, 2.0, 0.003710589456395429, 0.002630209857306292, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [2.0, 2.0, 3.0, 0.011093183383504531, 0.00786490624813104, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [3.0, 3.0, 4.0, 5.787747852263234e-05, 3.8584985681754894e-05, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [4.0, 4.0, 5.0, 0.0005916364471202417, 0.00041800401155234467, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [5.0, 5.0, 6.0, 0.0004372965043932221, 0.0003151107164009983, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [6.0, 6.0, 7.0, 0.0030160597141238405, 0.004019269341849468, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [7.0, 7.0, 8.0, 0.004733091576961934, 0.0063086451589669254, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [8.0, 8.0, 9.0, 0.004173609284576487, 0.0029517514046542496, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [9.0, 9.0, 10.0, 0.003260431290108289, 0.0023086683099583344, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [10.0, 10.0, 11.0, 0.0007459763898472612, 0.0005273281376506503, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [11.0, 11.0, 12.0, 0.008302202752524262, 0.005871348654573704, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [12.0, 12.0, 13.0, 0.007890629571918877, 0.005569099600066623, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [13.0, 13.0, 14.0, 0.003138245502116065, 0.0022186366767009066, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [14.0, 14.0, 15.0, 0.006154305216239905, 0.004353672551091344, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [15.0, 15.0, 16.0, 0.005530514614384868, 0.003916376046698122, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [16.0, 16.0, 17.0, 0.0025594707168897415, 0.00181349432704248, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [17.0, 17.0, 18.0, 0.005324728024082175, 0.003639850315978878, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [18.0, 18.0, 19.0, 0.0011961345561344017, 0.0008488696849986077, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [19.0, 19.0, 20.0, 0.0035948344993501644, 0.002540178224048864, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [20.0, 20.0, 21.0, 0.0023472532956400893, 0.0015819844129519507, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [21.0, 21.0, 22.0, 0.003684866132607592, 0.001974265100716459, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [22.0, 22.0, 23.0, 0.0016913085390502563, 0.0012282887108691974, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [23.0, 23.0, 24.0, 0.004392257536773099, 0.003196122980638697, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [24.0, 24.0, 25.0, 0.0025594707168897415, 0.00181349432704248, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [25.0, 25.0, 26.0, 0.00468807576033322, 0.0034083404018883487, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [26.0, 26.0, 27.0, 0.002154328367231315, 0.0015691227510580324, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [27.0, 27.0, 28.0, 0.003755605273024143, 0.0026623640120410877, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [28.0, 28.0, 29.0, 0.004212194270258243, 0.002977474728442086, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [29.0, 61.0, 62.0, 0.00264307151920021, 0.0018713718055651124, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [30.0, 60.0, 63.0, 0.0022700833242765795, 0.0016077077367397873, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [31.0, 63.0, 64.0, 0.006733080001466229, 0.00476524573169673, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [32.0, 64.0, 65.0, 0.004334380058250467, 0.003067506361699514, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [33.0, 65.0, 66.0, 0.0019421109459816632, 0.0013761978226492578, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [34.0, 66.0, 67.0, 0.002932458911813372, 0.0020771583958678055, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [35.0, 67.0, 68.0, 0.0014019211464370944, 0.000990347965831709, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [36.0, 70.0, 72.0, 0.004501581662871405, 0.003183261318744779, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [37.0, 42.0, 73.0, 0.0014855219487475634, 0.0010546562753013006, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [38.0, 73.0, 74.0, 0.00019292492840877447, 0.00041157318060538556, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [39.0, 43.0, 75.0, 0.0024372849288975176, 0.001723462693785052, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [40.0, 44.0, 76.0, 0.0035498186827214503, 0.0025144549002610274, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [41.0, 46.0, 77.0, 0.003318308768630921, 0.002803842292874189, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [42.0, 76.0, 78.0, 0.0010739487681421778, 0.0007073914041655063, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [43.0, 78.0, 79.0, 0.002668794842988047, 0.000649513925642874, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [44.0, 79.0, 80.0, 0.006450123439800027, 0.0015691227510580324, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [45.0, 79.0, 81.0, 0.009729847222749192, 0.002379407450374885, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [46.0, 81.0, 82.0, 0.00021221742124965192, 5.1446647575673195e-05, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [47.0, 47.0, 83.0, 0.0005466206304915277, 0.0003987115187114672, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [48.0, 49.0, 84.0, 0.00332473959957788, 0.0028874430951846583, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [49.0, 50.0, 85.0, 0.0009453321492029949, 0.00023150991409052937, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [50.0, 85.0, 86.0, 0.00023794074503748853, 0.00010289329515134639, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [51.0, 86.0, 87.0, 0.0, 6.43083094695915e-07, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [52.0, 7.0, 88.0, 0.001118964584770892, 0.0014855219487475634, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [53.0, 88.0, 89.0, 0.0030160597141238405, 0.004019269341849468, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [54.0, 89.0, 90.0, 0.0019228184531407855, 0.0025594707168897415, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [55.0, 90.0, 91.0, 0.0013633361607553395, 0.001819925157989439, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [56.0, 91.0, 92.0, 0.002025711748292132, 0.0027009489977228426, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [57.0, 92.0, 93.0, 0.0018006326651485618, 0.0023986999432157627, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [58.0, 93.0, 94.0, 0.0013247511750735846, 0.001762047679466807, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [59.0, 94.0, 95.0, 0.0013247511750735846, 0.001762047679466807, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [60.0, 89.0, 96.0, 0.004417980860560935, 0.0031253838402221464, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [61.0, 96.0, 97.0, 0.0062379060185503744, 0.0044115500296139755, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [62.0, 97.0, 98.0, 0.005800609514157153, 0.0012604428656039933, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [63.0, 97.0, 99.0, 0.00021221742124965192, 5.1446647575673195e-05, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [64.0, 131.0, 132.0, 0.0022314983385948246, 0.0015755535820049917, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [65.0, 131.0, 133.0, 0.005916364471202417, 0.004302225903515671, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [66.0, 121.0, 134.0, 0.005408328826392644, 0.003935668539538999, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [67.0, 16.0, 135.0, 0.0033890479090474715, 0.0023986999432157627, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [68.0, 16.0, 136.0, 0.0019421109459816632, 0.0013761978226492578, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [69.0, 18.0, 137.0, 0.003755605273024143, 0.0026623640120410877, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [70.0, 23.0, 138.0, 0.004945308998211585, 0.0035948344993501644, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [71.0, 29.0, 30.0, 0.002199344183860029, 0.001594846074845869, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [72.0, 30.0, 31.0, 0.0008231463612107711, 0.0005852056161732826, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [73.0, 31.0, 32.0, 0.0022314983385948246, 0.0015755535820049917, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [74.0, 2.0, 33.0, 0.002848858109502903, 0.0020192809173451725, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [75.0, 33.0, 34.0, 0.000128616618939183, 5.787747852263234e-05, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [76.0, 5.0, 35.0, 0.014623709573385104, 0.0035626803446153683, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [77.0, 5.0, 36.0, 0.008135001147903324, 0.010064250431991068, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [78.0, 6.0, 37.0, 0.00035369570208275316, 0.0004694506591280179, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [79.0, 37.0, 38.0, 0.013093171808008827, 0.009260396563621175, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [80.0, 38.0, 39.0, 0.006032119428247681, 0.004263640917833916, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [81.0, 39.0, 40.0, 0.0022314983385948246, 0.0015755535820049917, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [82.0, 40.0, 41.0, 0.005903502809308499, 0.004180040115523447, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [83.0, 41.0, 42.0, 0.014906666135051308, 0.010546562753013005, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [84.0, 42.0, 43.0, 0.007762012952979693, 0.0054919296287031134, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [85.0, 43.0, 44.0, 0.002848858109502903, 0.0020192809173451725, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [86.0, 44.0, 45.0, 0.0026044865335184556, 0.001852079312724235, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [87.0, 45.0, 46.0, 0.001028932951513464, 0.0008167155302638119, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [88.0, 46.0, 47.0, 0.004090008482266019, 0.002893873926131617, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [89.0, 47.0, 48.0, 0.0026816565048819654, 0.0018970951293529488, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [90.0, 48.0, 49.0, 0.004707368253174097, 0.003279723782949166, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [91.0, 49.0, 50.0, 0.005324728024082175, 0.0035755420065092867, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [92.0, 50.0, 51.0, 0.0025594707168897415, 0.00181349432704248, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [93.0, 51.0, 52.0, 0.0014469369630658085, 0.0010225021205665047, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [94.0, 38.0, 53.0, 0.005408328826392644, 0.0038263444134406933, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [95.0, 42.0, 54.0, 0.001035363782460423, 0.000733114727953343, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [96.0, 54.0, 55.0, 0.0033890479090474715, 0.0023986999432157627, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [97.0, 55.0, 56.0, 0.00574273203563452, 0.004064285158478183, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [98.0, 56.0, 57.0, 0.005575530431013582, 0.003942099370485958, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [99.0, 57.0, 58.0, 0.004334380058250467, 0.003067506361699514, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [100.0, 58.0, 59.0, 0.0030160597141238405, 0.0021350358743904376, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [101.0, 55.0, 60.0, 0.0021478975362843556, 0.001517676103482359, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [102.0, 60.0, 61.0, 0.002102881719655642, 0.0014919527796945224, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [103.0, 63.0, 69.0, 0.0023536841265870486, 0.0016655852152624197, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [104.0, 55.0, 70.0, 0.0014855219487475634, 0.0010546562753013006, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [105.0, 70.0, 71.0, 0.0007716997136350979, 0.0001864940974618153, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [106.0, 99.0, 100.0, 0.00021221742124965192, 5.1446647575673195e-05, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [107.0, 91.0, 101.0, 0.0014855219487475634, 0.0010546562753013006, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [108.0, 101.0, 102.0, 0.003717020287342388, 0.002630209857306292, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [109.0, 102.0, 103.0, 0.005717008711846684, 0.0013954903154901354, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [110.0, 103.0, 104.0, 0.004044992665637305, 0.0009839171348847498, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [111.0, 104.0, 105.0, 0.007524072207942205, 0.0018327868198833575, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [112.0, 104.0, 106.0, 0.000733114727953343, 0.00016720160462093786, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [113.0, 92.0, 107.0, 0.005459775473968318, 0.0013311820060205439, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [114.0, 94.0, 108.0, 0.003935668539538999, 0.0016720160462093787, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [115.0, 108.0, 109.0, 0.002906735588025535, 0.0012347195418161566, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [116.0, 94.0, 110.0, 0.00021221742124965192, 5.1446647575673195e-05, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [117.0, 7.0, 111.0, 0.0046237674508636285, 0.003273292952002207, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [118.0, 10.0, 112.0, 0.00688098911324629, 0.0016784468771563381, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [119.0, 11.0, 113.0, 0.0022314983385948246, 0.0015755535820049917, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [120.0, 13.0, 114.0, 0.00400640767995555, 0.002835996447608985, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [121.0, 114.0, 115.0, 0.004295795072568711, 0.0030417830379116774, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [122.0, 115.0, 116.0, 0.000257233237878366, 6.43083094695915e-05, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [123.0, 14.0, 117.0, 0.0032540004591613296, 0.0023536841265870486, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [124.0, 15.0, 118.0, 0.001035363782460423, 0.000733114727953343, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [125.0, 118.0, 119.0, 0.002971043897495127, 0.002102881719655642, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [126.0, 119.0, 120.0, 0.002726672321510679, 0.0019292492840877447, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [127.0, 120.0, 121.0, 0.003260431290108289, 0.0023086683099583344, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [128.0, 121.0, 122.0, 0.004707368253174097, 0.0033311704305248394, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [129.0, 122.0, 123.0, 0.003755605273024143, 0.0026623640120410877, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [130.0, 123.0, 124.0, 0.003922806877645081, 0.0027781189690863524, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [131.0, 124.0, 125.0, 0.0050353406314690135, 0.0035626803446153683, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [132.0, 125.0, 126.0, 0.005363313009763931, 0.003903514384804203, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [133.0, 126.0, 127.0, 0.0022314983385948246, 0.0015755535820049917, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [134.0, 127.0, 128.0, 0.003665573639766715, 0.0027009489977228426, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [135.0, 128.0, 129.0, 0.0037620361039711024, 0.0027331031524576387, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [136.0, 129.0, 130.0, 0.0006623755875367923, 0.0004694506591280179, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [137.0, 119.0, 131.0, 0.0022829449861704976, 0.0016270002295806648, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [138.0, 25.0, 139.0, 0.006109289399611192, 0.004327949227303507, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [139.0, 30.0, 140.0, 0.0033376012614717986, 0.002424423267003599, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [140.0, 31.0, 141.0, 0.003755605273024143, 0.0026623640120410877, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0]]) + + # Load data + self.loads = DataFrame( + ['id', 'bus_id', 'Pd', 'Qd', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [3.0, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [4.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [5.0, 5.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [6.0, 6.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [7.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [8.0, 8.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [9.0, 9.0, 0.0085, 0.00526782687642637, 0.0, 0.0, 0.0, 0.0085, 0.0085], + [10.0, 10.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [11.0, 11.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [12.0, 12.0, 0.02125, 0.013169567191065924, 0.0, 0.0, 0.0, 0.02125, 0.02125], + [13.0, 13.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [14.0, 14.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [15.0, 15.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [16.0, 16.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [17.0, 17.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [18.0, 18.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [19.0, 19.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [20.0, 20.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [21.0, 21.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [22.0, 22.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [23.0, 23.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [24.0, 24.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [25.0, 25.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [26.0, 26.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [27.0, 27.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [28.0, 28.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [29.0, 29.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [30.0, 30.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [31.0, 31.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [32.0, 32.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [33.0, 33.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [34.0, 34.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [35.0, 35.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [36.0, 36.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [37.0, 37.0, 0.0425, 0.026339134382131847, 0.0, 0.0, 0.0, 0.0425, 0.0425], + [38.0, 38.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [39.0, 39.0, 0.017, 0.01053565375285274, 0.0, 0.0, 0.0, 0.017, 0.017], + [40.0, 40.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [41.0, 41.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [42.0, 42.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [43.0, 43.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [44.0, 44.0, 0.0425, 0.026339134382131847, 0.0, 0.0, 0.0, 0.0425, 0.0425], + [45.0, 45.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [46.0, 46.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [47.0, 47.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [48.0, 48.0, 0.10625, 0.06584783595532961, 0.0, 0.0, 0.0, 0.10625, 0.10625], + [49.0, 49.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [50.0, 50.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [51.0, 51.0, 0.10625, 0.06584783595532961, 0.0, 0.0, 0.0, 0.10625, 0.10625], + [52.0, 52.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [53.0, 53.0, 0.085, 0.052678268764263694, 0.0, 0.0, 0.0, 0.085, 0.085], + [54.0, 54.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [55.0, 55.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [56.0, 56.0, 0.02125, 0.013169567191065924, 0.0, 0.0, 0.0, 0.02125, 0.02125], + [57.0, 57.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [58.0, 58.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [59.0, 59.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [60.0, 60.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [61.0, 61.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [62.0, 62.0, 0.17, 0.10535653752852739, 0.0, 0.0, 0.0, 0.17, 0.17], + [63.0, 63.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [64.0, 64.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [65.0, 65.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [66.0, 66.0, 0.19125, 0.11852610471959331, 0.0, 0.0, 0.0, 0.19125, 0.19125], + [67.0, 67.0, 0.0425, 0.026339134382131847, 0.0, 0.0, 0.0, 0.0425, 0.0425], + [68.0, 68.0, 0.085, 0.052678268764263694, 0.0, 0.0, 0.0, 0.085, 0.085], + [69.0, 69.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [70.0, 70.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [71.0, 71.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [72.0, 72.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [73.0, 73.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [74.0, 74.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [75.0, 75.0, 0.03825, 0.02370522094391866, 0.0, 0.0, 0.0, 0.03825, 0.03825], + [76.0, 76.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [77.0, 77.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [78.0, 78.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [79.0, 79.0, 0.4271249999999999, 0.26470830054042505, 0.0, 0.0, 0.0, 0.4271249999999999, 0.4271249999999999], + [80.0, 80.0, 0.6375, 0.3950870157319777, 0.0, 0.0, 0.0, 0.6375, 0.6375], + [81.0, 81.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [82.0, 82.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [83.0, 83.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [84.0, 84.0, 0.19125, 0.11852610471959331, 0.0, 0.0, 0.0, 0.19125, 0.19125], + [85.0, 85.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [86.0, 86.0, 0.425, 0.26339134382131846, 0.0, 0.0, 0.0, 0.425, 0.425], + [87.0, 87.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [88.0, 88.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [89.0, 89.0, 0.05525, 0.0342408746967714, 0.0, 0.0, 0.0, 0.05525, 0.05525], + [90.0, 90.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [91.0, 91.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [92.0, 92.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [93.0, 93.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [94.0, 94.0, 0.0935, 0.05794609564069006, 0.0, 0.0, 0.0, 0.0935, 0.0935], + [95.0, 95.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [96.0, 96.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [97.0, 97.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [98.0, 98.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [99.0, 99.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [100.0, 100.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [101.0, 101.0, 0.01275, 0.007901740314639553, 0.0, 0.0, 0.0, 0.01275, 0.01275], + [102.0, 102.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [103.0, 103.0, 0.10625, 0.06584783595532961, 0.0, 0.0, 0.0, 0.10625, 0.10625], + [104.0, 104.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [105.0, 105.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [106.0, 106.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [107.0, 107.0, 0.4271249999999999, 0.26470830054042505, 0.0, 0.0, 0.0, 0.4271249999999999, 0.4271249999999999], + [108.0, 108.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [109.0, 109.0, 0.6375, 0.3950870157319777, 0.0, 0.0, 0.0, 0.6375, 0.6375], + [110.0, 110.0, 0.6375, 0.3950870157319777, 0.0, 0.0, 0.0, 0.6375, 0.6375], + [111.0, 111.0, 0.02125, 0.013169567191065924, 0.0, 0.0, 0.0, 0.02125, 0.02125], + [112.0, 112.0, 0.425, 0.26339134382131846, 0.0, 0.0, 0.0, 0.425, 0.425], + [113.0, 113.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [114.0, 114.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [115.0, 115.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [116.0, 116.0, 0.255, 0.15803480629279107, 0.0, 0.0, 0.0, 0.255, 0.255], + [117.0, 117.0, 0.05525, 0.0342408746967714, 0.0, 0.0, 0.0, 0.05525, 0.05525], + [118.0, 118.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [119.0, 119.0, 0.0935, 0.05794609564069006, 0.0, 0.0, 0.0, 0.0935, 0.0935], + [120.0, 120.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [121.0, 121.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [122.0, 122.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [123.0, 123.0, 0.085, 0.052678268764263694, 0.0, 0.0, 0.0, 0.085, 0.085], + [124.0, 124.0, 0.10625, 0.06584783595532961, 0.0, 0.0, 0.0, 0.10625, 0.10625], + [125.0, 125.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [126.0, 126.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [127.0, 127.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [128.0, 128.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [129.0, 129.0, 0.0935, 0.05794609564069006, 0.0, 0.0, 0.0, 0.0935, 0.0935], + [130.0, 130.0, 0.095625, 0.059263052359796654, 0.0, 0.0, 0.0, 0.095625, 0.095625], + [131.0, 131.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [132.0, 132.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [133.0, 133.0, 0.03825, 0.02370522094391866, 0.0, 0.0, 0.0, 0.03825, 0.03825], + [134.0, 134.0, 0.029750000000000002, 0.018437394067492292, 0.0, 0.0, 0.0, 0.029750000000000002, 0.029750000000000002], + [135.0, 135.0, 0.02125, 0.013169567191065924, 0.0, 0.0, 0.0, 0.02125, 0.02125], + [136.0, 136.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375], + [137.0, 137.0, 0.04675, 0.02897304782034503, 0.0, 0.0, 0.0, 0.04675, 0.04675], + [138.0, 138.0, 0.0425, 0.026339134382131847, 0.0, 0.0, 0.0, 0.0425, 0.0425], + [139.0, 139.0, 0.0425, 0.026339134382131847, 0.0, 0.0, 0.0, 0.0425, 0.0425], + [140.0, 140.0, 0.1275, 0.07901740314639553, 0.0, 0.0, 0.0, 0.1275, 0.1275], + [141.0, 141.0, 0.06375, 0.03950870157319777, 0.0, 0.0, 0.0, 0.06375, 0.06375]]) + + self.real_params = True + super().__init__(*args, **kwargs) diff --git a/powergrid_case/distribution/Case33bw.py b/powergrid_case/distribution/Case33bw.py new file mode 100644 index 0000000000000000000000000000000000000000..d900fa917d17036d0be2203c4cbba9b7dc759924 --- /dev/null +++ b/powergrid_case/distribution/Case33bw.py @@ -0,0 +1,184 @@ +"""Power System Case: 33bw + +Data Source: MATPOWER case file +Base MVA: 100.0 MVA +Base kV: 12.66 kV + +Unit conversions applied: + - Pd/Qd converted from kW/kVar to MW/MVAr (divided by 1000) + - r/x converted from Ohms to p.u. (Z_pu = Z_ohm * Sbase / Vbase^2) + + +Nodes (bus) columns: + id, type, Pd, Qd, Gs, Bs, Vm, Va, baseKV, Vmax, Vmin + - type: 1=PQ, 2=PV, 3=Slack + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - Gs/Bs: Shunt conductance/susceptance (MW/MVAr at V=1.0 p.u.) + - Vm: Voltage magnitude (p.u.) + - Va: Voltage angle (degrees) + - baseKV: Base voltage (kV) + - Vmax/Vmin: Voltage limits (p.u.) + +Units (generators) columns: + id, bus_id, Pg, Qg, Qmax, Qmin, Vg, mBase, status, Pmax, Pmin, mc_a, mc_b, mc_c + - Pg/Qg: Active/Reactive power output (MW/MVAr) + - Qmax/Qmin: Reactive power limits (MVAr) + - Vg: Voltage setpoint (p.u.) + - mBase: Machine base (MVA) + - status: >0 in-service, <=0 out-of-service + - Pmax/Pmin: Active power limits (MW) + - mc_a/mc_b/mc_c: Marginal cost coefficients (quadratic) + +Lines (branches) columns: + id, from, to, r, x, b, rateA, ratio, angle, status, floor, cap + - r/x: Resistance/Reactance (p.u.) + - b: Line charging susceptance (p.u.) + - rateA: Long-term rating (MVA) + - ratio: Transformer tap ratio (0 for line) + - angle: Transformer phase shift (degrees) + - status: 1=in-service, 0=out-of-service + - floor/cap: Power flow limits (MW) + +Loads columns: + id, bus_id, Pd, Qd, mc_a, mc_b, mc_c, d_max, d_min + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - mc_a/mc_b/mc_c: Marginal utility coefficients + - d_max/d_min: Demand limits (MW) +""" +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case33bw(ClearCase): + GRID_TYPE = "distribution" + BUS_COUNT = 33 + VOLTAGE_LEVEL = "MV" + SOURCE = "MATPOWER" + DESCRIPTION = "IEEE 33-bus Baran & Wu radial distribution" + + def __init__(self, *args, **kwargs): + # System base values + self.baseMVA = 100.0 + self.baseKV = 12.66 + + # Node (bus) data + self.nodes = DataFrame( + ['id', 'type', 'Pd', 'Qd', 'Gs', 'Bs', 'Vm', 'Va', 'baseKV', 'Vmax', 'Vmin'], + [[1.0, 3.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 12.66, 1.0, 1.0], + [2.0, 1.0, 0.1, 0.06, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [3.0, 1.0, 0.09, 0.04, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [4.0, 1.0, 0.12, 0.08, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [5.0, 1.0, 0.06, 0.03, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [6.0, 1.0, 0.06, 0.02, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [7.0, 1.0, 0.2, 0.1, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [8.0, 1.0, 0.2, 0.1, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [9.0, 1.0, 0.06, 0.02, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [10.0, 1.0, 0.06, 0.02, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [11.0, 1.0, 0.045, 0.03, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [12.0, 1.0, 0.06, 0.035, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [13.0, 1.0, 0.06, 0.035, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [14.0, 1.0, 0.12, 0.08, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [15.0, 1.0, 0.06, 0.01, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [16.0, 1.0, 0.06, 0.02, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [17.0, 1.0, 0.06, 0.02, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [18.0, 1.0, 0.09, 0.04, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [19.0, 1.0, 0.09, 0.04, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [20.0, 1.0, 0.09, 0.04, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [21.0, 1.0, 0.09, 0.04, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [22.0, 1.0, 0.09, 0.04, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [23.0, 1.0, 0.09, 0.05, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [24.0, 1.0, 0.42, 0.2, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [25.0, 1.0, 0.42, 0.2, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [26.0, 1.0, 0.06, 0.025, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [27.0, 1.0, 0.06, 0.025, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [28.0, 1.0, 0.06, 0.02, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [29.0, 1.0, 0.12, 0.07, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [30.0, 1.0, 0.2, 0.6, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [31.0, 1.0, 0.15, 0.07, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [32.0, 1.0, 0.21, 0.1, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9], + [33.0, 1.0, 0.06, 0.04, 0.0, 0.0, 1.0, 0.0, 12.66, 1.1, 0.9]]) + + # Generator (unit) data + self.units = DataFrame( + ['id', 'bus_id', 'Pg', 'Qg', 'Qmax', 'Qmin', 'Vg', 'mBase', 'status', 'Pmax', 'Pmin', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min'], + [[1.0, 1.0, 0.0, 0.0, 10.0, -10.0, 1.0, 100.0, 1.0, 10.0, 0.0, 0.0, 0.0, 20.0, 10.0, 0.0]]) + + # Branch (line) data + self.lines = DataFrame( + ['id', 'from', 'to', 'r', 'x', 'b', 'rateA', 'ratio', 'angle', 'status', 'floor', 'cap'], + [[1.0, 1.0, 2.0, 0.05752591161723931, 0.02932448856844086, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [2.0, 2.0, 3.0, 0.3075951673242839, 0.156667639990117, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [3.0, 3.0, 4.0, 0.22835665566062455, 0.11629967381185907, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [4.0, 4.0, 5.0, 0.23777792751984705, 0.12110389853477384, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [5.0, 5.0, 6.0, 0.5109948114372992, 0.44111517910399334, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [6.0, 6.0, 7.0, 0.11679881404281126, 0.386084968641515, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [7.0, 7.0, 8.0, 0.4438604503742304, 0.14668483537107332, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [8.0, 8.0, 9.0, 0.642643047350938, 0.461704713630771, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [9.0, 9.0, 10.0, 0.6513780013926013, 0.461704713630771, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [10.0, 10.0, 11.0, 0.12266371175649943, 0.04055514376486502, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [11.0, 11.0, 12.0, 0.2335976280856225, 0.0772419507398506, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [12.0, 12.0, 13.0, 0.9159223237972591, 0.7206337084372169, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [13.0, 13.0, 14.0, 0.33791793635462913, 0.4447963383072657, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [14.0, 14.0, 15.0, 0.36873984561592654, 0.3281847018510615, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [15.0, 15.0, 16.0, 0.4656354429495194, 0.340039282336176, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [16.0, 16.0, 17.0, 0.8042396971217077, 1.0737754218358877, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [17.0, 17.0, 18.0, 0.4567133113212491, 0.3581331157081926, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [18.0, 2.0, 19.0, 0.10232374734519789, 0.09764430768002116, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [19.0, 19.0, 20.0, 0.9385084192478456, 0.8456683362907391, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [20.0, 20.0, 21.0, 0.2554974057186496, 0.29848585810940653, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [21.0, 21.0, 22.0, 0.4423006371525048, 0.5848051730893535, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [22.0, 3.0, 23.0, 0.28151509025703225, 0.19235616650319826, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [23.0, 23.0, 24.0, 0.5602849092438275, 0.4424254222102428, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [24.0, 24.0, 25.0, 0.559037058666447, 0.43743401990072095, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [25.0, 6.0, 26.0, 0.12665683360411692, 0.06451387485056989, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [26.0, 26.0, 27.0, 0.17731956704576368, 0.09028198927347643, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [27.0, 27.0, 28.0, 0.6607368807229547, 0.5825590420500687, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [28.0, 28.0, 29.0, 0.5017607171646838, 0.4371220572563759, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [29.0, 29.0, 30.0, 0.3166420840102922, 0.16128468712642474, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [30.0, 30.0, 31.0, 0.6079528012997611, 0.6008400530086925, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [31.0, 31.0, 32.0, 0.19372880213831675, 0.2257985619769946, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [32.0, 32.0, 33.0, 0.2127585234433688, 0.3308051880635605, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [33.0, 21.0, 8.0, 1.247850577380462, 1.247850577380462, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [34.0, 9.0, 15.0, 1.247850577380462, 1.247850577380462, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [35.0, 12.0, 22.0, 1.247850577380462, 1.247850577380462, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [36.0, 18.0, 33.0, 0.3119626443451155, 0.3119626443451155, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [37.0, 25.0, 29.0, 0.3119626443451155, 0.3119626443451155, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]) + + # Load data + self.loads = DataFrame( + ['id', 'bus_id', 'Pd', 'Qd', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2.0, 2.0, 0.1, 0.06, 0.0, 0.0, 0.0, 0.1, 0.1], + [3.0, 3.0, 0.09, 0.04, 0.0, 0.0, 0.0, 0.09, 0.09], + [4.0, 4.0, 0.12, 0.08, 0.0, 0.0, 0.0, 0.12, 0.12], + [5.0, 5.0, 0.06, 0.03, 0.0, 0.0, 0.0, 0.06, 0.06], + [6.0, 6.0, 0.06, 0.02, 0.0, 0.0, 0.0, 0.06, 0.06], + [7.0, 7.0, 0.2, 0.1, 0.0, 0.0, 0.0, 0.2, 0.2], + [8.0, 8.0, 0.2, 0.1, 0.0, 0.0, 0.0, 0.2, 0.2], + [9.0, 9.0, 0.06, 0.02, 0.0, 0.0, 0.0, 0.06, 0.06], + [10.0, 10.0, 0.06, 0.02, 0.0, 0.0, 0.0, 0.06, 0.06], + [11.0, 11.0, 0.045, 0.03, 0.0, 0.0, 0.0, 0.045, 0.045], + [12.0, 12.0, 0.06, 0.035, 0.0, 0.0, 0.0, 0.06, 0.06], + [13.0, 13.0, 0.06, 0.035, 0.0, 0.0, 0.0, 0.06, 0.06], + [14.0, 14.0, 0.12, 0.08, 0.0, 0.0, 0.0, 0.12, 0.12], + [15.0, 15.0, 0.06, 0.01, 0.0, 0.0, 0.0, 0.06, 0.06], + [16.0, 16.0, 0.06, 0.02, 0.0, 0.0, 0.0, 0.06, 0.06], + [17.0, 17.0, 0.06, 0.02, 0.0, 0.0, 0.0, 0.06, 0.06], + [18.0, 18.0, 0.09, 0.04, 0.0, 0.0, 0.0, 0.09, 0.09], + [19.0, 19.0, 0.09, 0.04, 0.0, 0.0, 0.0, 0.09, 0.09], + [20.0, 20.0, 0.09, 0.04, 0.0, 0.0, 0.0, 0.09, 0.09], + [21.0, 21.0, 0.09, 0.04, 0.0, 0.0, 0.0, 0.09, 0.09], + [22.0, 22.0, 0.09, 0.04, 0.0, 0.0, 0.0, 0.09, 0.09], + [23.0, 23.0, 0.09, 0.05, 0.0, 0.0, 0.0, 0.09, 0.09], + [24.0, 24.0, 0.42, 0.2, 0.0, 0.0, 0.0, 0.42, 0.42], + [25.0, 25.0, 0.42, 0.2, 0.0, 0.0, 0.0, 0.42, 0.42], + [26.0, 26.0, 0.06, 0.025, 0.0, 0.0, 0.0, 0.06, 0.06], + [27.0, 27.0, 0.06, 0.025, 0.0, 0.0, 0.0, 0.06, 0.06], + [28.0, 28.0, 0.06, 0.02, 0.0, 0.0, 0.0, 0.06, 0.06], + [29.0, 29.0, 0.12, 0.07, 0.0, 0.0, 0.0, 0.12, 0.12], + [30.0, 30.0, 0.2, 0.6, 0.0, 0.0, 0.0, 0.2, 0.2], + [31.0, 31.0, 0.15, 0.07, 0.0, 0.0, 0.0, 0.15, 0.15], + [32.0, 32.0, 0.21, 0.1, 0.0, 0.0, 0.0, 0.21, 0.21], + [33.0, 33.0, 0.06, 0.04, 0.0, 0.0, 0.0, 0.06, 0.06]]) + + self.real_params = True + super().__init__(*args, **kwargs) diff --git a/powergrid_case/distribution/Case533mt_hi.py b/powergrid_case/distribution/Case533mt_hi.py new file mode 100644 index 0000000000000000000000000000000000000000..23d6bb37043764e2b4ed9ad8995048f2ae9363a2 --- /dev/null +++ b/powergrid_case/distribution/Case533mt_hi.py @@ -0,0 +1,1722 @@ +"""Power System Case: 533mt_hi + +Data Source: MATPOWER case file +Base MVA: 16.666666666666668 MVA +Base kV: 6.92820323027551 kV + +All values are in standard MATPOWER units (MW, MVAr, p.u.) + + +Nodes (bus) columns: + id, type, Pd, Qd, Gs, Bs, Vm, Va, baseKV, Vmax, Vmin + - type: 1=PQ, 2=PV, 3=Slack + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - Gs/Bs: Shunt conductance/susceptance (MW/MVAr at V=1.0 p.u.) + - Vm: Voltage magnitude (p.u.) + - Va: Voltage angle (degrees) + - baseKV: Base voltage (kV) + - Vmax/Vmin: Voltage limits (p.u.) + +Units (generators) columns: + id, bus_id, Pg, Qg, Qmax, Qmin, Vg, mBase, status, Pmax, Pmin, mc_a, mc_b, mc_c + - Pg/Qg: Active/Reactive power output (MW/MVAr) + - Qmax/Qmin: Reactive power limits (MVAr) + - Vg: Voltage setpoint (p.u.) + - mBase: Machine base (MVA) + - status: >0 in-service, <=0 out-of-service + - Pmax/Pmin: Active power limits (MW) + - mc_a/mc_b/mc_c: Marginal cost coefficients (quadratic) + +Lines (branches) columns: + id, from, to, r, x, b, rateA, ratio, angle, status, floor, cap + - r/x: Resistance/Reactance (p.u.) + - b: Line charging susceptance (p.u.) + - rateA: Long-term rating (MVA) + - ratio: Transformer tap ratio (0 for line) + - angle: Transformer phase shift (degrees) + - status: 1=in-service, 0=out-of-service + - floor/cap: Power flow limits (MW) + +Loads columns: + id, bus_id, Pd, Qd, mc_a, mc_b, mc_c, d_max, d_min + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - mc_a/mc_b/mc_c: Marginal utility coefficients + - d_max/d_min: Demand limits (MW) +""" +from math import inf + +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case533mt_hi(ClearCase): + GRID_TYPE = "distribution" + BUS_COUNT = 533 + VOLTAGE_LEVEL = "MV" + SOURCE = "MATPOWER" + DESCRIPTION = "533-bus Swedish distribution (high load)" + + def __init__(self, *args, **kwargs): + # System base values + self.baseMVA = 16.666666666666668 + self.baseKV = 6.92820323027551 + + # Node (bus) data + self.nodes = DataFrame( + ['id', 'type', 'Pd', 'Qd', 'Gs', 'Bs', 'Vm', 'Va', 'baseKV', 'Vmax', 'Vmin'], + [[2.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [3.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [4.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 77.94228634059948, 1.05, 0.95], + [5.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [6.0, 1.0, 0.011666667, 0.000116667, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [7.0, 1.0, 0.001333333, 1.33e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [8.0, 1.0, -0.01, -0.0001, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [9.0, 1.0, 0.015430667, 0.000154307, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [10.0, 1.0, 0.001333333, 1.33e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [11.0, 1.0, 0.005120333, 5.12e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [12.0, 1.0, 0.0045, 4.5e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [13.0, 1.0, 0.012233333, 0.000122333, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [14.0, 1.0, 0.013601333, 0.000136013, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [15.0, 1.0, 0.003033333, 3.03e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [16.0, 1.0, 0.003533333, 3.53e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [17.0, 1.0, 0.010909333, 0.000109093, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [18.0, 1.0, 0.003145, 3.15e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [19.0, 1.0, 0.010404333, 0.000104043, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [20.0, 1.0, 0.011139333, 0.000111393, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [21.0, 1.0, 0.002033333, 2.03e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [22.0, 1.0, 0.043089, 0.00043089, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [23.0, 1.0, 0.135866, 0.00135866, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [24.0, 1.0, 0.036602333, 0.000366023, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [25.0, 1.0, 0.060565667, 0.000605657, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [26.0, 1.0, 0.026843, 0.00026843, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [27.0, 1.0, 0.002333333, 2.33e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [28.0, 1.0, 0.116758667, 0.001167587, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [29.0, 1.0, 0.01372, 0.0001372, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [30.0, 1.0, 0.137666667, 0.001376667, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [31.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [32.0, 1.0, 0.073793667, 0.000737937, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [33.0, 1.0, 0.091932333, 0.000919323, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [34.0, 1.0, 0.152158667, 0.001521587, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [35.0, 1.0, 0.104275, 0.00104275, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [36.0, 1.0, 0.114037, 0.00114037, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [37.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [38.0, 1.0, 0.127620333, 0.001276203, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [39.0, 1.0, 0.045260333, 0.000452603, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [40.0, 1.0, 0.104846333, 0.001048463, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [41.0, 1.0, 0.008302667, 8.3e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [42.0, 1.0, 0.001666667, 1.67e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [43.0, 1.0, 0.001, 1e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [44.0, 1.0, 0.128162333, 0.001281623, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [45.0, 1.0, 0.022831667, 0.000228317, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [46.0, 1.0, 0.021797, 0.00021797, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [47.0, 1.0, -0.020333333, -0.000203333, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [48.0, 1.0, 0.011620333, 0.000116203, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [49.0, 1.0, 0.0133, 0.000133, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [50.0, 1.0, 0.014470667, 0.000144707, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [51.0, 1.0, 0.002515, 2.52e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [52.0, 1.0, -0.011666667, -0.000116667, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [53.0, 1.0, 0.009918, 9.92e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [54.0, 1.0, 0.008893333, 8.89e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [55.0, 1.0, 0.003348667, 3.35e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [56.0, 1.0, 0.038106, 0.00038106, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [57.0, 1.0, 0.098204667, 0.000982047, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [58.0, 1.0, 0.02217, 0.0002217, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [59.0, 1.0, 0.013351, 0.00013351, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [60.0, 1.0, 0.134312333, 0.001343123, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [61.0, 1.0, 0.121267, 0.00121267, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [62.0, 1.0, 0.098485667, 0.000984857, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [63.0, 1.0, 0.211801667, 0.002118017, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [64.0, 1.0, 0.078207667, 0.000782077, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [65.0, 1.0, 0.029, 0.00029, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [66.0, 1.0, 0.146945, 0.00146945, 0.0, 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0.95], + [433.0, 1.0, 0.006438667, 6.44e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [434.0, 1.0, 0.000974, 9.74e-06, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [435.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [436.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [437.0, 1.0, 0.002040667, 2.04e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [438.0, 1.0, 0.012589, 0.00012589, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [439.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [440.0, 1.0, 0.002322333, 2.32e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [441.0, 1.0, 0.001551667, 1.55e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [442.0, 1.0, 0.006957, 6.96e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [443.0, 1.0, -0.033666667, -0.000336667, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [444.0, 1.0, 0.003155667, 3.16e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [445.0, 1.0, 0.010319333, 0.000103193, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [446.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [447.0, 1.0, 0.002059667, 2.06e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [448.0, 1.0, 0.004118667, 4.12e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [449.0, 1.0, 0.008922333, 8.92e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [450.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [451.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [452.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [453.0, 1.0, 0.006126333, 6.13e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [454.0, 1.0, 0.024109333, 0.000241093, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [455.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [456.0, 1.0, 0.004596333, 4.6e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [457.0, 1.0, 0.002900333, 2.9e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [458.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [459.0, 1.0, 0.002996667, 3e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [460.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [461.0, 1.0, 0.003531333, 3.53e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [462.0, 1.0, 0.012311667, 0.000123117, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [463.0, 1.0, 0.039695, 0.00039695, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [464.0, 1.0, 0.008241333, 8.24e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [465.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [466.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [467.0, 1.0, 0.00209, 2.09e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [468.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [469.0, 1.0, 0.003464333, 3.46e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [470.0, 1.0, 0.009515333, 9.52e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [471.0, 1.0, 0.004315333, 4.32e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [472.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [473.0, 1.0, 0.002697333, 2.7e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [474.0, 1.0, 0.010859, 0.00010859, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [475.0, 1.0, 0.010397, 0.00010397, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [476.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [477.0, 1.0, 0.010208, 0.00010208, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [478.0, 1.0, 0.005962667, 5.96e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [479.0, 1.0, 0.012755333, 0.000127553, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [480.0, 1.0, 0.009580333, 9.58e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [481.0, 1.0, 0.003293, 3.29e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [482.0, 1.0, 0.000926667, 9.27e-06, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [483.0, 1.0, 0.010494333, 0.000104943, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [484.0, 1.0, 0.006432333, 6.43e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [485.0, 1.0, 0.004755333, 4.76e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [486.0, 1.0, 0.013455, 0.00013455, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [487.0, 1.0, 0.028033, 0.00028033, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [488.0, 1.0, 0.004785667, 4.79e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [489.0, 1.0, 0.013807333, 0.000138073, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [490.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [491.0, 1.0, 0.007254667, 7.25e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [492.0, 1.0, 0.006442667, 6.44e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [493.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [494.0, 1.0, 0.013007667, 0.000130077, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [495.0, 1.0, 0.000200333, 2e-06, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [496.0, 1.0, 0.024303667, 0.000243037, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [497.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [498.0, 1.0, 0.015787667, 0.000157877, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [499.0, 1.0, 0.022333333, 0.000223333, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [500.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [501.0, 1.0, 0.003176, 3.18e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [502.0, 1.0, 0.024355333, 0.000243553, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [503.0, 1.0, 0.001566, 1.57e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [504.0, 1.0, 0.004946333, 4.95e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [505.0, 1.0, 0.005344333, 5.34e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [506.0, 1.0, 0.006171667, 6.17e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [507.0, 1.0, 0.058623667, 0.000586237, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [508.0, 1.0, 0.074241333, 0.000742413, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [509.0, 1.0, 0.223894667, 0.002238947, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [510.0, 1.0, 0.050518333, 0.000505183, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [511.0, 1.0, 0.198641333, 0.001986413, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [512.0, 1.0, 0.228844, 0.00228844, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [513.0, 1.0, 0.011762, 0.00011762, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [514.0, 1.0, 0.020129333, 0.000201293, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [515.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [516.0, 1.0, 0.017023667, 0.000170237, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [517.0, 1.0, 0.056277333, 0.000562773, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [518.0, 1.0, 0.007604, 7.6e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [519.0, 1.0, 0.008273, 8.27e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [520.0, 1.0, 0.027617, 0.00027617, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [521.0, 1.0, 0.007689333, 7.69e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [522.0, 1.0, 0.019396667, 0.000193967, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [523.0, 1.0, 0.014603, 0.00014603, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [524.0, 1.0, 0.007695, 7.7e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [525.0, 1.0, 0.009764333, 9.76e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [526.0, 1.0, 0.019030667, 0.000190307, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [527.0, 1.0, 0.02092, 0.0002092, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [528.0, 1.0, 0.007255667, 7.26e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [529.0, 1.0, 0.00732, 7.32e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [530.0, 1.0, 0.015935667, 0.000159357, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [531.0, 1.0, 0.022209333, 0.000222093, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [532.0, 1.0, 0.010216667, 0.000102167, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [533.0, 1.0, 0.015608667, 0.000156087, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95]]) + + # Generator (unit) data + self.units = DataFrame( + ['id', 'bus_id', 'Pg', 'Qg', 'Qmax', 'Qmin', 'Vg', 'mBase', 'status', 'Pmax', 'Pmin', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min'], + [[1.0, 1.0, 0.0, 0.0, 16.666666666666668, -16.666666666666668, 1.0, 16.666666666666668, 1.0, 16.666666666666668, -16.666666666666668, 0.0, 0.0, 0.0, 16.666666666666668, -16.666666666666668]]) + + # Branch (line) data + self.lines = DataFrame( + ['id', 'from', 'to', 'r', 'x', 'b', 'rateA', 'ratio', 'angle', 'status', 'floor', 'cap'], + [[1.0, 1.0, 2.0, 0.000289183, 0.000475417, 0.0, 53.00075471, 0.0, 0.0, 1.0, -53.00075471, 53.00075471], + [2.0, 1.0, 3.0, 0.000328467, 0.000662892, 0.0, 54.55960044, 0.0, 0.0, 1.0, -54.55960044, 54.55960044], + [3.0, 4.0, 1.0, 0.000961394, 0.001996898, 0.0, 50.66248612, 0.0, 0.0, 1.0, -50.66248612, 50.66248612], + [4.0, 5.0, 2.0, 0.247364266, 0.139251062, 0.0, 5.40399852, 0.0, 0.0, 1.0, -5.40399852, 5.40399852], + [5.0, 5.0, 6.0, 0.027863723, 0.004373436, 0.0, 1.662768775, 0.0, 0.0, 1.0, -1.662768775, 1.662768775], + [6.0, 6.0, 7.0, 0.398977986, 0.066484391, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [7.0, 7.0, 8.0, 0.067883681, 0.012975432, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [8.0, 5.0, 9.0, 0.208766667, 0.063536421, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [9.0, 9.0, 10.0, 0.066111111, 0.020120374, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [10.0, 11.0, 10.0, 0.095, 0.029226847, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [11.0, 11.0, 12.0, 0.090711111, 0.028244336, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [12.0, 12.0, 13.0, 0.067577778, 0.020566742, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [13.0, 13.0, 14.0, 0.156288264, 0.029873274, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [14.0, 14.0, 15.0, 0.075133333, 0.022866213, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [15.0, 15.0, 16.0, 0.219155556, 0.066698194, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [16.0, 16.0, 17.0, 0.0978, 0.029764627, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [17.0, 17.0, 18.0, 0.235416667, 0.023420137, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [18.0, 12.0, 19.0, 0.294904514, 0.052741123, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [19.0, 11.0, 20.0, 0.139822222, 0.043160902, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [20.0, 20.0, 21.0, 0.137592431, 0.026299712, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [21.0, 5.0, 22.0, 0.239918542, 0.041684789, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [22.0, 5.0, 23.0, 0.043220833, 0.024010276, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [23.0, 24.0, 23.0, 0.090162882, 0.014582553, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [24.0, 24.0, 25.0, 0.04400441, 0.008386089, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [25.0, 25.0, 26.0, 0.074835486, 0.012553608, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [26.0, 26.0, 27.0, 0.169541493, 0.026580165, 0.0, 0.831384388, 0.0, 0.0, 1.0, -0.831384388, 0.831384388], + [27.0, 2.0, 3.0, 0.032371494, 0.017194544, 0.0, 7.343895424, 0.0, 0.0, 0.0, -7.343895424, 7.343895424], + [28.0, 28.0, 2.0, 0.015817569, 0.008259662, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [29.0, 29.0, 28.0, 0.04492691, 0.022563835, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [30.0, 29.0, 30.0, 0.049522083, 0.026264914, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [31.0, 31.0, 30.0, 0.044647396, 0.026960865, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [32.0, 31.0, 32.0, 0.00984809, 0.006746897, 0.0, 2.355589098, 0.0, 0.0, 1.0, -2.355589098, 2.355589098], + [33.0, 32.0, 33.0, 0.014038229, 0.008455466, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [34.0, 34.0, 33.0, 0.04824875, 0.025954464, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [35.0, 34.0, 35.0, 0.033796771, 0.016953801, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [36.0, 36.0, 2.0, 0.090628368, 0.047669523, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [37.0, 36.0, 34.0, 0.014013646, 0.009037206, 0.0, 1.80133284, 0.0, 0.0, 0.0, -1.80133284, 1.80133284], + [38.0, 36.0, 37.0, 0.170242083, 0.085905542, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [39.0, 38.0, 2.0, 0.025255833, 0.014019794, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [40.0, 38.0, 39.0, 0.021056806, 0.010625128, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [41.0, 40.0, 39.0, 0.020606771, 0.010398344, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [42.0, 6.0, 41.0, 0.142377674, 0.024212407, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [43.0, 42.0, 41.0, 0.149054757, 0.025026167, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [44.0, 42.0, 43.0, 0.074605278, 0.014260213, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [45.0, 5.0, 44.0, 0.135366736, 0.022557072, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [46.0, 44.0, 22.0, 0.101668611, 0.016544849, 0.0, 0.969948452, 0.0, 0.0, 0.0, -0.969948452, 0.969948452], + [47.0, 22.0, 45.0, 0.183953646, 0.030653436, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [48.0, 5.0, 46.0, 0.042744444, 0.013008921, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [49.0, 23.0, 46.0, 0.052677778, 0.016032049, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [50.0, 5.0, 47.0, 0.506677778, 0.154203221, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [51.0, 5.0, 48.0, 0.263688889, 0.080251548, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [52.0, 49.0, 48.0, 0.074255556, 0.022599069, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [53.0, 50.0, 49.0, 0.099855556, 0.030390218, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [54.0, 51.0, 50.0, 0.145711111, 0.04434598, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [55.0, 52.0, 51.0, 0.075566667, 0.022998094, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [56.0, 52.0, 17.0, 0.1074, 0.033507049, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [57.0, 49.0, 53.0, 0.109838021, 0.01830305, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [58.0, 53.0, 54.0, 0.244916667, 0.024365233, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [59.0, 55.0, 48.0, 0.416416667, 0.041426699, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [60.0, 5.0, 56.0, 0.0834, 0.025382105, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [61.0, 56.0, 57.0, 0.114890347, 0.018636517, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [62.0, 57.0, 58.0, 0.15733434, 0.025462281, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [63.0, 59.0, 58.0, 0.557958333, 0.055507797, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [64.0, 57.0, 25.0, 0.219097604, 0.046946193, 0.0, 0.969948452, 0.0, 0.0, 0.0, -0.969948452, 0.969948452], + [65.0, 60.0, 2.0, 0.084021528, 0.046676104, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [66.0, 61.0, 60.0, 0.0304425, 0.016911586, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [67.0, 62.0, 61.0, 0.022760694, 0.012644147, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [68.0, 63.0, 2.0, 0.050245903, 0.02779055, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [69.0, 64.0, 63.0, 0.09060441, 0.049270645, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [70.0, 65.0, 64.0, 0.036736667, 0.016807521, 0.0, 1.835973856, 0.0, 0.0, 1.0, -1.835973856, 1.835973856], + [71.0, 65.0, 66.0, 0.028608229, 0.014435945, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [72.0, 67.0, 66.0, 0.165348924, 0.035577555, 0.0, 1.039230485, 0.0, 0.0, 0.0, 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72.0, 76.0, 0.049057639, 0.027252771, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [83.0, 75.0, 76.0, 0.048884444, 0.027444975, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [84.0, 77.0, 2.0, 0.574452639, 0.105789533, 0.0, 0.831384388, 0.0, 0.0, 1.0, -0.831384388, 0.831384388], + [85.0, 75.0, 77.0, 0.222536944, 0.036927022, 0.0, 0.969948452, 0.0, 0.0, 0.0, -0.969948452, 0.969948452], + [86.0, 75.0, 78.0, 0.647027222, 0.139436645, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [87.0, 78.0, 79.0, 0.238282847, 0.039368737, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [88.0, 80.0, 79.0, 0.247356632, 0.046012115, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [89.0, 81.0, 2.0, 0.046489327, 0.025826008, 0.0, 4.156921938, 0.0, 0.0, 1.0, -4.156921938, 4.156921938], + [90.0, 77.0, 82.0, 0.154396424, 0.024971407, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [91.0, 83.0, 3.0, 0.071801944, 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1.073871501], + [508.0, 469.0, 470.0, 0.133125694, 0.081176573, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [509.0, 471.0, 470.0, 0.097166667, 0.029571877, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [510.0, 108.0, 471.0, 0.169511111, 0.051589315, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [511.0, 108.0, 472.0, 0.06104191, 0.05264873, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [512.0, 472.0, 473.0, 0.213125, 0.021202478, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [513.0, 472.0, 474.0, 0.020292188, 0.020484166, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [514.0, 474.0, 475.0, 0.103854375, 0.10483691, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [515.0, 475.0, 476.0, 0.062738125, 0.063331672, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [516.0, 476.0, 477.0, 0.099128924, 0.034905931, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [517.0, 478.0, 477.0, 0.469875, 0.046744935, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [518.0, 477.0, 479.0, 0.085144444, 0.025913012, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [519.0, 479.0, 480.0, 0.110633333, 0.033670347, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [520.0, 480.0, 481.0, 0.083044444, 0.025273895, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [521.0, 481.0, 482.0, 0.069488889, 0.021148373, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [522.0, 483.0, 482.0, 0.279235625, 0.045509787, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [523.0, 484.0, 477.0, 0.087755556, 0.026707683, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [524.0, 485.0, 484.0, 0.222391389, 0.037058576, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [525.0, 486.0, 484.0, 0.166259375, 0.02702446, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [526.0, 487.0, 486.0, 0.273960729, 0.044624251, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [527.0, 476.0, 488.0, 0.054679063, 0.055196365, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [528.0, 488.0, 489.0, 0.094940417, 0.074747652, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [529.0, 474.0, 490.0, 0.12913, 0.130351661, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [530.0, 490.0, 491.0, 0.054424688, 0.054939583, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [531.0, 490.0, 492.0, 0.014441563, 0.01457819, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [532.0, 493.0, 471.0, 0.092366667, 0.028111037, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [533.0, 493.0, 494.0, 0.079679861, 0.015230179, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [534.0, 493.0, 495.0, 0.168522222, 0.051288354, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [535.0, 495.0, 496.0, 0.259152743, 0.035106425, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [536.0, 480.0, 495.0, 0.168188889, 0.051186907, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [537.0, 495.0, 497.0, 0.101677778, 0.030944797, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [538.0, 498.0, 497.0, 0.1968, 0.059894464, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [539.0, 499.0, 497.0, 0.047696632, 0.007948011, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [540.0, 468.0, 500.0, 0.016754306, 0.011081095, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [541.0, 500.0, 501.0, 0.00670625, 0.006769696, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [542.0, 500.0, 502.0, 0.064761563, 0.065374252, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [543.0, 465.0, 503.0, 0.157962639, 0.03356879, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [544.0, 503.0, 504.0, 0.399791667, 0.039772781, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [545.0, 267.0, 505.0, 0.170510451, 0.029247246, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [546.0, 506.0, 505.0, 0.142507951, 0.028424869, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [547.0, 267.0, 507.0, 0.108311111, 0.032963597, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [548.0, 507.0, 508.0, 0.037244444, 0.011335041, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [549.0, 508.0, 509.0, 0.052833333, 0.016087354, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [550.0, 267.0, 510.0, 0.106677778, 0.032536864, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [551.0, 510.0, 511.0, 0.064555556, 0.019711312, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [552.0, 511.0, 509.0, 0.046688889, 0.014667747, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [553.0, 510.0, 512.0, 0.056566667, 0.017274505, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [554.0, 512.0, 306.0, 0.325790764, 0.034065773, 0.0, 0.6443229, 0.0, 0.0, 0.0, -0.6443229, 0.6443229], + [555.0, 266.0, 513.0, 0.0991925, 0.035374879, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [556.0, 514.0, 513.0, 0.117133333, 0.035648568, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [557.0, 514.0, 515.0, 0.164478819, 0.027408214, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [558.0, 516.0, 514.0, 0.136722222, 0.041610286, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [559.0, 517.0, 516.0, 0.1214, 0.036947093, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [560.0, 498.0, 517.0, 0.132688889, 0.040382774, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [561.0, 498.0, 518.0, 0.129577778, 0.039435933, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [562.0, 519.0, 518.0, 0.0712, 0.021669135, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [563.0, 519.0, 520.0, 0.069722222, 0.021219386, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [564.0, 520.0, 521.0, 0.167577778, 0.051000921, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [565.0, 522.0, 521.0, 0.148133333, 0.045083164, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [566.0, 522.0, 523.0, 0.119133333, 0.036257252, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [567.0, 523.0, 524.0, 0.1228, 0.037373172, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [568.0, 524.0, 525.0, 0.050988889, 0.01551805, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [569.0, 525.0, 526.0, 0.256511285, 0.042744204, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [570.0, 525.0, 527.0, 0.132933333, 0.040457168, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [571.0, 527.0, 528.0, 0.081733333, 0.024874869, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [572.0, 348.0, 528.0, 0.164233333, 0.049983066, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [573.0, 529.0, 524.0, 0.144044444, 0.043838744, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [574.0, 529.0, 530.0, 0.061611111, 0.018750836, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [575.0, 530.0, 531.0, 0.113799757, 0.01896322, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [576.0, 532.0, 521.0, 0.214245347, 0.035701146, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [577.0, 517.0, 533.0, 0.560425521, 0.059721458, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323]]) + + # Load data + self.loads = DataFrame( + ['id', 'bus_id', 'Pd', 'Qd', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2.0, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [3.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [4.0, 5.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [5.0, 6.0, 0.011666667, 0.000116667, 0.0, 0.0, 0.0, 0.011666667, 0.011666667], + [6.0, 7.0, 0.001333333, 1.33e-05, 0.0, 0.0, 0.0, 0.001333333, 0.001333333], + [7.0, 8.0, -0.01, -0.0001, 0.0, 0.0, 0.0, -0.01, -0.01], + [8.0, 9.0, 0.015430667, 0.000154307, 0.0, 0.0, 0.0, 0.015430667, 0.015430667], + [9.0, 10.0, 0.001333333, 1.33e-05, 0.0, 0.0, 0.0, 0.001333333, 0.001333333], + [10.0, 11.0, 0.005120333, 5.12e-05, 0.0, 0.0, 0.0, 0.005120333, 0.005120333], + [11.0, 12.0, 0.0045, 4.5e-05, 0.0, 0.0, 0.0, 0.0045, 0.0045], + [12.0, 13.0, 0.012233333, 0.000122333, 0.0, 0.0, 0.0, 0.012233333, 0.012233333], + [13.0, 14.0, 0.013601333, 0.000136013, 0.0, 0.0, 0.0, 0.013601333, 0.013601333], + [14.0, 15.0, 0.003033333, 3.03e-05, 0.0, 0.0, 0.0, 0.003033333, 0.003033333], + [15.0, 16.0, 0.003533333, 3.53e-05, 0.0, 0.0, 0.0, 0.003533333, 0.003533333], + [16.0, 17.0, 0.010909333, 0.000109093, 0.0, 0.0, 0.0, 0.010909333, 0.010909333], + [17.0, 18.0, 0.003145, 3.15e-05, 0.0, 0.0, 0.0, 0.003145, 0.003145], + [18.0, 19.0, 0.010404333, 0.000104043, 0.0, 0.0, 0.0, 0.010404333, 0.010404333], + [19.0, 20.0, 0.011139333, 0.000111393, 0.0, 0.0, 0.0, 0.011139333, 0.011139333], + [20.0, 21.0, 0.002033333, 2.03e-05, 0.0, 0.0, 0.0, 0.002033333, 0.002033333], + [21.0, 22.0, 0.043089, 0.00043089, 0.0, 0.0, 0.0, 0.043089, 0.043089], + [22.0, 23.0, 0.135866, 0.00135866, 0.0, 0.0, 0.0, 0.135866, 0.135866], + [23.0, 24.0, 0.036602333, 0.000366023, 0.0, 0.0, 0.0, 0.036602333, 0.036602333], + [24.0, 25.0, 0.060565667, 0.000605657, 0.0, 0.0, 0.0, 0.060565667, 0.060565667], + [25.0, 26.0, 0.026843, 0.00026843, 0.0, 0.0, 0.0, 0.026843, 0.026843], + [26.0, 27.0, 0.002333333, 2.33e-05, 0.0, 0.0, 0.0, 0.002333333, 0.002333333], + [27.0, 28.0, 0.116758667, 0.001167587, 0.0, 0.0, 0.0, 0.116758667, 0.116758667], + [28.0, 29.0, 0.01372, 0.0001372, 0.0, 0.0, 0.0, 0.01372, 0.01372], + [29.0, 30.0, 0.137666667, 0.001376667, 0.0, 0.0, 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9.27e-06, 0.0, 0.0, 0.0, 0.000926667, 0.000926667], + [482.0, 483.0, 0.010494333, 0.000104943, 0.0, 0.0, 0.0, 0.010494333, 0.010494333], + [483.0, 484.0, 0.006432333, 6.43e-05, 0.0, 0.0, 0.0, 0.006432333, 0.006432333], + [484.0, 485.0, 0.004755333, 4.76e-05, 0.0, 0.0, 0.0, 0.004755333, 0.004755333], + [485.0, 486.0, 0.013455, 0.00013455, 0.0, 0.0, 0.0, 0.013455, 0.013455], + [486.0, 487.0, 0.028033, 0.00028033, 0.0, 0.0, 0.0, 0.028033, 0.028033], + [487.0, 488.0, 0.004785667, 4.79e-05, 0.0, 0.0, 0.0, 0.004785667, 0.004785667], + [488.0, 489.0, 0.013807333, 0.000138073, 0.0, 0.0, 0.0, 0.013807333, 0.013807333], + [489.0, 490.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [490.0, 491.0, 0.007254667, 7.25e-05, 0.0, 0.0, 0.0, 0.007254667, 0.007254667], + [491.0, 492.0, 0.006442667, 6.44e-05, 0.0, 0.0, 0.0, 0.006442667, 0.006442667], + [492.0, 493.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [493.0, 494.0, 0.013007667, 0.000130077, 0.0, 0.0, 0.0, 0.013007667, 0.013007667], + [494.0, 495.0, 0.000200333, 2e-06, 0.0, 0.0, 0.0, 0.000200333, 0.000200333], + [495.0, 496.0, 0.024303667, 0.000243037, 0.0, 0.0, 0.0, 0.024303667, 0.024303667], + [496.0, 497.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [497.0, 498.0, 0.015787667, 0.000157877, 0.0, 0.0, 0.0, 0.015787667, 0.015787667], + [498.0, 499.0, 0.022333333, 0.000223333, 0.0, 0.0, 0.0, 0.022333333, 0.022333333], + [499.0, 500.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [500.0, 501.0, 0.003176, 3.18e-05, 0.0, 0.0, 0.0, 0.003176, 0.003176], + [501.0, 502.0, 0.024355333, 0.000243553, 0.0, 0.0, 0.0, 0.024355333, 0.024355333], + [502.0, 503.0, 0.001566, 1.57e-05, 0.0, 0.0, 0.0, 0.001566, 0.001566], + [503.0, 504.0, 0.004946333, 4.95e-05, 0.0, 0.0, 0.0, 0.004946333, 0.004946333], + [504.0, 505.0, 0.005344333, 5.34e-05, 0.0, 0.0, 0.0, 0.005344333, 0.005344333], + [505.0, 506.0, 0.006171667, 6.17e-05, 0.0, 0.0, 0.0, 0.006171667, 0.006171667], + [506.0, 507.0, 0.058623667, 0.000586237, 0.0, 0.0, 0.0, 0.058623667, 0.058623667], + [507.0, 508.0, 0.074241333, 0.000742413, 0.0, 0.0, 0.0, 0.074241333, 0.074241333], + [508.0, 509.0, 0.223894667, 0.002238947, 0.0, 0.0, 0.0, 0.223894667, 0.223894667], + [509.0, 510.0, 0.050518333, 0.000505183, 0.0, 0.0, 0.0, 0.050518333, 0.050518333], + [510.0, 511.0, 0.198641333, 0.001986413, 0.0, 0.0, 0.0, 0.198641333, 0.198641333], + [511.0, 512.0, 0.228844, 0.00228844, 0.0, 0.0, 0.0, 0.228844, 0.228844], + [512.0, 513.0, 0.011762, 0.00011762, 0.0, 0.0, 0.0, 0.011762, 0.011762], + [513.0, 514.0, 0.020129333, 0.000201293, 0.0, 0.0, 0.0, 0.020129333, 0.020129333], + [514.0, 515.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [515.0, 516.0, 0.017023667, 0.000170237, 0.0, 0.0, 0.0, 0.017023667, 0.017023667], + [516.0, 517.0, 0.056277333, 0.000562773, 0.0, 0.0, 0.0, 0.056277333, 0.056277333], + [517.0, 518.0, 0.007604, 7.6e-05, 0.0, 0.0, 0.0, 0.007604, 0.007604], + [518.0, 519.0, 0.008273, 8.27e-05, 0.0, 0.0, 0.0, 0.008273, 0.008273], + [519.0, 520.0, 0.027617, 0.00027617, 0.0, 0.0, 0.0, 0.027617, 0.027617], + [520.0, 521.0, 0.007689333, 7.69e-05, 0.0, 0.0, 0.0, 0.007689333, 0.007689333], + [521.0, 522.0, 0.019396667, 0.000193967, 0.0, 0.0, 0.0, 0.019396667, 0.019396667], + [522.0, 523.0, 0.014603, 0.00014603, 0.0, 0.0, 0.0, 0.014603, 0.014603], + [523.0, 524.0, 0.007695, 7.7e-05, 0.0, 0.0, 0.0, 0.007695, 0.007695], + [524.0, 525.0, 0.009764333, 9.76e-05, 0.0, 0.0, 0.0, 0.009764333, 0.009764333], + [525.0, 526.0, 0.019030667, 0.000190307, 0.0, 0.0, 0.0, 0.019030667, 0.019030667], + [526.0, 527.0, 0.02092, 0.0002092, 0.0, 0.0, 0.0, 0.02092, 0.02092], + [527.0, 528.0, 0.007255667, 7.26e-05, 0.0, 0.0, 0.0, 0.007255667, 0.007255667], + [528.0, 529.0, 0.00732, 7.32e-05, 0.0, 0.0, 0.0, 0.00732, 0.00732], + [529.0, 530.0, 0.015935667, 0.000159357, 0.0, 0.0, 0.0, 0.015935667, 0.015935667], + [530.0, 531.0, 0.022209333, 0.000222093, 0.0, 0.0, 0.0, 0.022209333, 0.022209333], + [531.0, 532.0, 0.010216667, 0.000102167, 0.0, 0.0, 0.0, 0.010216667, 0.010216667], + [532.0, 533.0, 0.015608667, 0.000156087, 0.0, 0.0, 0.0, 0.015608667, 0.015608667]]) + + self.real_params = True + super().__init__(*args, **kwargs) diff --git a/powergrid_case/distribution/Case533mt_lo.py b/powergrid_case/distribution/Case533mt_lo.py new file mode 100644 index 0000000000000000000000000000000000000000..ab27342203e348d13992f8190cd42cb6f32f2e33 --- /dev/null +++ b/powergrid_case/distribution/Case533mt_lo.py @@ -0,0 +1,1724 @@ +"""Power System Case: 533mt_lo + +Data Source: MATPOWER case file +Base MVA: 16.666666666666668 MVA +Base kV: 77.94228634059948 kV + +All values are in standard MATPOWER units (MW, MVAr, p.u.) + + +Nodes (bus) columns: + id, type, Pd, Qd, Gs, Bs, Vm, Va, baseKV, Vmax, Vmin + - type: 1=PQ, 2=PV, 3=Slack + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - Gs/Bs: Shunt conductance/susceptance (MW/MVAr at V=1.0 p.u.) + - Vm: Voltage magnitude (p.u.) + - Va: Voltage angle (degrees) + - baseKV: Base voltage (kV) + - Vmax/Vmin: Voltage limits (p.u.) + +Units (generators) columns: + id, bus_id, Pg, Qg, Qmax, Qmin, Vg, mBase, status, Pmax, Pmin, mc_a, mc_b, mc_c + - Pg/Qg: Active/Reactive power output (MW/MVAr) + - Qmax/Qmin: Reactive power limits (MVAr) + - Vg: Voltage setpoint (p.u.) + - mBase: Machine base (MVA) + - status: >0 in-service, <=0 out-of-service + - Pmax/Pmin: Active power limits (MW) + - mc_a/mc_b/mc_c: Marginal cost coefficients (quadratic) + +Lines (branches) columns: + id, from, to, r, x, b, rateA, ratio, angle, status, floor, cap + - r/x: Resistance/Reactance (p.u.) + - b: Line charging susceptance (p.u.) + - rateA: Long-term rating (MVA) + - ratio: Transformer tap ratio (0 for line) + - angle: Transformer phase shift (degrees) + - status: 1=in-service, 0=out-of-service + - floor/cap: Power flow limits (MW) + +Loads columns: + id, bus_id, Pd, Qd, mc_a, mc_b, mc_c, d_max, d_min + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - mc_a/mc_b/mc_c: Marginal utility coefficients + - d_max/d_min: Demand limits (MW) +""" +from math import inf + +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case533mt_lo(ClearCase): + GRID_TYPE = "distribution" + BUS_COUNT = 533 + VOLTAGE_LEVEL = "MV" + SOURCE = "MATPOWER" + DESCRIPTION = "533-bus Swedish distribution (low load)" + + def __init__(self, *args, **kwargs): + # System base values + self.baseMVA = 16.666666666666668 + self.baseKV = 77.94228634059948 + + # Node (bus) data + self.nodes = DataFrame( + ['id', 'type', 'Pd', 'Qd', 'Gs', 'Bs', 'Vm', 'Va', 'baseKV', 'Vmax', 'Vmin'], + [[1.0, 3.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 77.94228634059948, 1.0, 1.0], + [2.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [3.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [4.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 77.94228634059948, 1.05, 0.95], + [5.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [6.0, 1.0, -0.015666667, -0.000156667, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [7.0, 1.0, -0.224666667, -0.002246667, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [8.0, 1.0, -0.205333333, -0.002053333, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [9.0, 1.0, 0.004427333, 4.43e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [10.0, 1.0, 3.33e-05, 3.33e-07, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [11.0, 1.0, -0.001271, -1.27e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [12.0, 1.0, 0.000933333, 9.33e-06, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [13.0, 1.0, 0.002866667, 2.87e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [14.0, 1.0, 0.002033333, 2.03e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [15.0, 1.0, 0.000966667, 9.67e-06, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [16.0, 1.0, 0.000633333, 6.33e-06, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [17.0, 1.0, 0.002332333, 2.33e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [18.0, 1.0, -0.000740333, -7.4e-06, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [19.0, 1.0, 0.000566667, 5.67e-06, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [20.0, 1.0, 0.002306667, 2.31e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [21.0, 1.0, 0.0006, 6e-06, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [22.0, 1.0, 0.007484333, 7.48e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [23.0, 1.0, 0.034165333, 0.000341653, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [24.0, 1.0, 0.015535333, 0.000155353, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [25.0, 1.0, 0.017548667, 0.000175487, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [26.0, 1.0, 0.007739333, 7.74e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [27.0, 1.0, 0.001166667, 1.17e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [28.0, 1.0, 0.002838, 2.84e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [29.0, 1.0, 0.008333333, 8.33e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [30.0, 1.0, 0.090333333, 0.000903333, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [31.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [32.0, 1.0, 0.019124333, 0.000191243, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [33.0, 1.0, -0.018339, -0.00018339, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [34.0, 1.0, 0.107100667, 0.001071007, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [35.0, 1.0, 0.081759667, 0.000817597, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [36.0, 1.0, 0.074532333, 0.000745323, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [37.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [38.0, 1.0, 0.019531, 0.00019531, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [39.0, 1.0, 0.009567, 9.57e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [40.0, 1.0, 0.016669667, 0.000166697, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [41.0, 1.0, 0.000260333, 2.6e-06, 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6.92820323027551, 1.05, 0.95], + [527.0, 1.0, -0.03656, -0.0003656, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [528.0, 1.0, 0.001296, 1.3e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [529.0, 1.0, 0.003147667, 3.15e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [530.0, 1.0, 0.003143, 3.14e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [531.0, 1.0, 0.005816333, 5.82e-05, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [532.0, 1.0, -0.000495, -4.95e-06, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95], + [533.0, 1.0, -0.000610333, -6.1e-06, 0.0, 0.0, 1.0, 0.0, 6.92820323027551, 1.05, 0.95]]) + + # Generator (unit) data + self.units = DataFrame( + ['id', 'bus_id', 'Pg', 'Qg', 'Qmax', 'Qmin', 'Vg', 'mBase', 'status', 'Pmax', 'Pmin', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min'], + [[1.0, 1.0, 0.0, 0.0, 16.666666666666668, -16.666666666666668, 1.0, 16.666666666666668, 1.0, 16.666666666666668, -16.666666666666668, 0.0, 0.0, 0.0, 16.666666666666668, -16.666666666666668]]) + + # Branch (line) data + self.lines = DataFrame( + ['id', 'from', 'to', 'r', 'x', 'b', 'rateA', 'ratio', 'angle', 'status', 'floor', 'cap'], + [[1.0, 1.0, 2.0, 0.000289183, 0.000475417, 0.0, 53.00075471, 0.0, 0.0, 1.0, -53.00075471, 53.00075471], + [2.0, 1.0, 3.0, 0.000328467, 0.000662892, 0.0, 54.55960044, 0.0, 0.0, 1.0, -54.55960044, 54.55960044], + [3.0, 4.0, 1.0, 0.000961394, 0.001996898, 0.0, 50.66248612, 0.0, 0.0, 1.0, -50.66248612, 50.66248612], + [4.0, 5.0, 2.0, 0.247364266, 0.139251062, 0.0, 5.40399852, 0.0, 0.0, 1.0, -5.40399852, 5.40399852], + [5.0, 5.0, 6.0, 0.027863723, 0.004373436, 0.0, 1.662768775, 0.0, 0.0, 1.0, -1.662768775, 1.662768775], + [6.0, 6.0, 7.0, 0.398977986, 0.066484391, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [7.0, 7.0, 8.0, 0.067883681, 0.012975432, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [8.0, 5.0, 9.0, 0.208766667, 0.063536421, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [9.0, 9.0, 10.0, 0.066111111, 0.020120374, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [10.0, 11.0, 10.0, 0.095, 0.029226847, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [11.0, 11.0, 12.0, 0.090711111, 0.028244336, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [12.0, 12.0, 13.0, 0.067577778, 0.020566742, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [13.0, 13.0, 14.0, 0.156288264, 0.029873274, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [14.0, 14.0, 15.0, 0.075133333, 0.022866213, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [15.0, 15.0, 16.0, 0.219155556, 0.066698194, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [16.0, 16.0, 17.0, 0.0978, 0.029764627, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [17.0, 17.0, 18.0, 0.235416667, 0.023420137, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [18.0, 12.0, 19.0, 0.294904514, 0.052741123, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [19.0, 11.0, 20.0, 0.139822222, 0.043160902, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [20.0, 20.0, 21.0, 0.137592431, 0.026299712, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [21.0, 5.0, 22.0, 0.239918542, 0.041684789, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [22.0, 5.0, 23.0, 0.043220833, 0.024010276, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [23.0, 24.0, 23.0, 0.090162882, 0.014582553, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [24.0, 24.0, 25.0, 0.04400441, 0.008386089, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [25.0, 25.0, 26.0, 0.074835486, 0.012553608, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [26.0, 26.0, 27.0, 0.169541493, 0.026580165, 0.0, 0.831384388, 0.0, 0.0, 1.0, -0.831384388, 0.831384388], + [27.0, 2.0, 3.0, 0.032371494, 0.017194544, 0.0, 7.343895424, 0.0, 0.0, 0.0, -7.343895424, 7.343895424], + [28.0, 28.0, 2.0, 0.015817569, 0.008259662, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [29.0, 29.0, 28.0, 0.04492691, 0.022563835, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [30.0, 29.0, 30.0, 0.049522083, 0.026264914, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [31.0, 31.0, 30.0, 0.044647396, 0.026960865, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [32.0, 31.0, 32.0, 0.00984809, 0.006746897, 0.0, 2.355589098, 0.0, 0.0, 1.0, -2.355589098, 2.355589098], + [33.0, 32.0, 33.0, 0.014038229, 0.008455466, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [34.0, 34.0, 33.0, 0.04824875, 0.025954464, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [35.0, 34.0, 35.0, 0.033796771, 0.016953801, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [36.0, 36.0, 2.0, 0.090628368, 0.047669523, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [37.0, 36.0, 34.0, 0.014013646, 0.009037206, 0.0, 1.80133284, 0.0, 0.0, 0.0, -1.80133284, 1.80133284], + [38.0, 36.0, 37.0, 0.170242083, 0.085905542, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [39.0, 38.0, 2.0, 0.025255833, 0.014019794, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [40.0, 38.0, 39.0, 0.021056806, 0.010625128, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [41.0, 40.0, 39.0, 0.020606771, 0.010398344, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [42.0, 6.0, 41.0, 0.142377674, 0.024212407, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [43.0, 42.0, 41.0, 0.149054757, 0.025026167, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [44.0, 42.0, 43.0, 0.074605278, 0.014260213, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [45.0, 5.0, 44.0, 0.135366736, 0.022557072, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [46.0, 44.0, 22.0, 0.101668611, 0.016544849, 0.0, 0.969948452, 0.0, 0.0, 0.0, -0.969948452, 0.969948452], + [47.0, 22.0, 45.0, 0.183953646, 0.030653436, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [48.0, 5.0, 46.0, 0.042744444, 0.013008921, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [49.0, 23.0, 46.0, 0.052677778, 0.016032049, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [50.0, 5.0, 47.0, 0.506677778, 0.154203221, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [51.0, 5.0, 48.0, 0.263688889, 0.080251548, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [52.0, 49.0, 48.0, 0.074255556, 0.022599069, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [53.0, 50.0, 49.0, 0.099855556, 0.030390218, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [54.0, 51.0, 50.0, 0.145711111, 0.04434598, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [55.0, 52.0, 51.0, 0.075566667, 0.022998094, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [56.0, 52.0, 17.0, 0.1074, 0.033507049, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [57.0, 49.0, 53.0, 0.109838021, 0.01830305, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [58.0, 53.0, 54.0, 0.244916667, 0.024365233, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [59.0, 55.0, 48.0, 0.416416667, 0.041426699, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [60.0, 5.0, 56.0, 0.0834, 0.025382105, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [61.0, 56.0, 57.0, 0.114890347, 0.018636517, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [62.0, 57.0, 58.0, 0.15733434, 0.025462281, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [63.0, 59.0, 58.0, 0.557958333, 0.055507797, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [64.0, 57.0, 25.0, 0.219097604, 0.046946193, 0.0, 0.969948452, 0.0, 0.0, 0.0, -0.969948452, 0.969948452], + [65.0, 60.0, 2.0, 0.084021528, 0.046676104, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [66.0, 61.0, 60.0, 0.0304425, 0.016911586, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [67.0, 62.0, 61.0, 0.022760694, 0.012644147, 0.0, 2.078460969, 0.0, 0.0, 1.0, -2.078460969, 2.078460969], + [68.0, 63.0, 2.0, 0.050245903, 0.02779055, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [69.0, 64.0, 63.0, 0.09060441, 0.049270645, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [70.0, 65.0, 64.0, 0.036736667, 0.016807521, 0.0, 1.835973856, 0.0, 0.0, 1.0, -1.835973856, 1.835973856], + [71.0, 65.0, 66.0, 0.028608229, 0.014435945, 0.0, 1.80133284, 0.0, 0.0, 1.0, -1.80133284, 1.80133284], + [72.0, 67.0, 66.0, 0.165348924, 0.035577555, 0.0, 1.039230485, 0.0, 0.0, 0.0, -1.039230485, 1.039230485], + [73.0, 68.0, 67.0, 0.142671424, 0.03071594, 0.0, 1.039230485, 0.0, 0.0, 1.0, -1.039230485, 1.039230485], + [74.0, 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451.0, 453.0, 0.05693375, 0.057472383, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [492.0, 451.0, 454.0, 0.184338542, 0.022021256, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [493.0, 452.0, 455.0, 0.038113542, 0.05815808, 0.0, 1.905255888, 0.0, 0.0, 1.0, -1.905255888, 1.905255888], + [494.0, 452.0, 456.0, 0.119553646, 0.041967205, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [495.0, 266.0, 457.0, 0.19304625, 0.074222744, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [496.0, 457.0, 458.0, 0.229295694, 0.151653404, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [497.0, 458.0, 459.0, 0.035299514, 0.006747225, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [498.0, 458.0, 460.0, 0.100675, 0.050077641, 0.0, 1.143153533, 0.0, 0.0, 1.0, -1.143153533, 1.143153533], + [499.0, 459.0, 461.0, 0.167906389, 0.02715645, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [500.0, 462.0, 461.0, 0.129891528, 0.021610885, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [501.0, 460.0, 463.0, 0.243535486, 0.039866811, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [502.0, 460.0, 464.0, 0.026378333, 0.017446311, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [503.0, 464.0, 465.0, 0.043483611, 0.028759535, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [504.0, 465.0, 466.0, 0.115857778, 0.076626935, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [505.0, 466.0, 467.0, 0.090790972, 0.060048053, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [506.0, 467.0, 468.0, 0.094485417, 0.062491514, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [507.0, 468.0, 469.0, 0.212763056, 0.140718916, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [508.0, 469.0, 470.0, 0.133125694, 0.081176573, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [509.0, 471.0, 470.0, 0.097166667, 0.029571877, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [510.0, 108.0, 471.0, 0.169511111, 0.051589315, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [511.0, 108.0, 472.0, 0.06104191, 0.05264873, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [512.0, 472.0, 473.0, 0.213125, 0.021202478, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [513.0, 472.0, 474.0, 0.020292188, 0.020484166, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [514.0, 474.0, 475.0, 0.103854375, 0.10483691, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [515.0, 475.0, 476.0, 0.062738125, 0.063331672, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [516.0, 476.0, 477.0, 0.099128924, 0.034905931, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [517.0, 478.0, 477.0, 0.469875, 0.046744935, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [518.0, 477.0, 479.0, 0.085144444, 0.025913012, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [519.0, 479.0, 480.0, 0.110633333, 0.033670347, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [520.0, 480.0, 481.0, 0.083044444, 0.025273895, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [521.0, 481.0, 482.0, 0.069488889, 0.021148373, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [522.0, 483.0, 482.0, 0.279235625, 0.045509787, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [523.0, 484.0, 477.0, 0.087755556, 0.026707683, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [524.0, 485.0, 484.0, 0.222391389, 0.037058576, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [525.0, 486.0, 484.0, 0.166259375, 0.02702446, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [526.0, 487.0, 486.0, 0.273960729, 0.044624251, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [527.0, 476.0, 488.0, 0.054679063, 0.055196365, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [528.0, 488.0, 489.0, 0.094940417, 0.074747652, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [529.0, 474.0, 490.0, 0.12913, 0.130351661, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [530.0, 490.0, 491.0, 0.054424688, 0.054939583, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [531.0, 490.0, 492.0, 0.014441563, 0.01457819, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [532.0, 493.0, 471.0, 0.092366667, 0.028111037, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [533.0, 493.0, 494.0, 0.079679861, 0.015230179, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [534.0, 493.0, 495.0, 0.168522222, 0.051288354, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [535.0, 495.0, 496.0, 0.259152743, 0.035106425, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [536.0, 480.0, 495.0, 0.168188889, 0.051186907, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [537.0, 495.0, 497.0, 0.101677778, 0.030944797, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [538.0, 498.0, 497.0, 0.1968, 0.059894464, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [539.0, 499.0, 497.0, 0.047696632, 0.007948011, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [540.0, 468.0, 500.0, 0.016754306, 0.011081095, 0.0, 1.073871501, 0.0, 0.0, 1.0, -1.073871501, 1.073871501], + [541.0, 500.0, 501.0, 0.00670625, 0.006769696, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [542.0, 500.0, 502.0, 0.064761563, 0.065374252, 0.0, 1.454922678, 0.0, 0.0, 1.0, -1.454922678, 1.454922678], + [543.0, 465.0, 503.0, 0.157962639, 0.03356879, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [544.0, 503.0, 504.0, 0.399791667, 0.039772781, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323], + [545.0, 267.0, 505.0, 0.170510451, 0.029247246, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [546.0, 506.0, 505.0, 0.142507951, 0.028424869, 0.0, 0.969948452, 0.0, 0.0, 1.0, -0.969948452, 0.969948452], + [547.0, 267.0, 507.0, 0.108311111, 0.032963597, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [548.0, 507.0, 508.0, 0.037244444, 0.011335041, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [549.0, 508.0, 509.0, 0.052833333, 0.016087354, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [550.0, 267.0, 510.0, 0.106677778, 0.032536864, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [551.0, 510.0, 511.0, 0.064555556, 0.019711312, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [552.0, 511.0, 509.0, 0.046688889, 0.014667747, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [553.0, 510.0, 512.0, 0.056566667, 0.017274505, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [554.0, 512.0, 306.0, 0.325790764, 0.034065773, 0.0, 0.6443229, 0.0, 0.0, 0.0, -0.6443229, 0.6443229], + [555.0, 266.0, 513.0, 0.0991925, 0.035374879, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [556.0, 514.0, 513.0, 0.117133333, 0.035648568, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [557.0, 514.0, 515.0, 0.164478819, 0.027408214, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [558.0, 516.0, 514.0, 0.136722222, 0.041610286, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [559.0, 517.0, 516.0, 0.1214, 0.036947093, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [560.0, 498.0, 517.0, 0.132688889, 0.040382774, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [561.0, 498.0, 518.0, 0.129577778, 0.039435933, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [562.0, 519.0, 518.0, 0.0712, 0.021669135, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [563.0, 519.0, 520.0, 0.069722222, 0.021219386, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [564.0, 520.0, 521.0, 0.167577778, 0.051000921, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [565.0, 522.0, 521.0, 0.148133333, 0.045083164, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [566.0, 522.0, 523.0, 0.119133333, 0.036257252, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [567.0, 523.0, 524.0, 0.1228, 0.037373172, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [568.0, 524.0, 525.0, 0.050988889, 0.01551805, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [569.0, 525.0, 526.0, 0.256511285, 0.042744204, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [570.0, 525.0, 527.0, 0.132933333, 0.040457168, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [571.0, 527.0, 528.0, 0.081733333, 0.024874869, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [572.0, 348.0, 528.0, 0.164233333, 0.049983066, 0.0, 1.420281662, 0.0, 0.0, 0.0, -1.420281662, 1.420281662], + [573.0, 529.0, 524.0, 0.144044444, 0.043838744, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [574.0, 529.0, 530.0, 0.061611111, 0.018750836, 0.0, 1.420281662, 0.0, 0.0, 1.0, -1.420281662, 1.420281662], + [575.0, 530.0, 531.0, 0.113799757, 0.01896322, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [576.0, 532.0, 521.0, 0.214245347, 0.035701146, 0.0, 1.004589468, 0.0, 0.0, 1.0, -1.004589468, 1.004589468], + [577.0, 517.0, 533.0, 0.560425521, 0.059721458, 0.0, 0.692820323, 0.0, 0.0, 1.0, -0.692820323, 0.692820323]]) + + # Load data + self.loads = DataFrame( + ['id', 'bus_id', 'Pd', 'Qd', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [3.0, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [4.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [5.0, 5.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [6.0, 6.0, -0.015666667, -0.000156667, 0.0, 0.0, 0.0, -0.015666667, -0.015666667], + [7.0, 7.0, -0.224666667, -0.002246667, 0.0, 0.0, 0.0, -0.224666667, -0.224666667], + [8.0, 8.0, -0.205333333, -0.002053333, 0.0, 0.0, 0.0, -0.205333333, -0.205333333], + [9.0, 9.0, 0.004427333, 4.43e-05, 0.0, 0.0, 0.0, 0.004427333, 0.004427333], + [10.0, 10.0, 3.33e-05, 3.33e-07, 0.0, 0.0, 0.0, 3.33e-05, 3.33e-05], + [11.0, 11.0, -0.001271, -1.27e-05, 0.0, 0.0, 0.0, -0.001271, -0.001271], + [12.0, 12.0, 0.000933333, 9.33e-06, 0.0, 0.0, 0.0, 0.000933333, 0.000933333], + [13.0, 13.0, 0.002866667, 2.87e-05, 0.0, 0.0, 0.0, 0.002866667, 0.002866667], + [14.0, 14.0, 0.002033333, 2.03e-05, 0.0, 0.0, 0.0, 0.002033333, 0.002033333], + [15.0, 15.0, 0.000966667, 9.67e-06, 0.0, 0.0, 0.0, 0.000966667, 0.000966667], + [16.0, 16.0, 0.000633333, 6.33e-06, 0.0, 0.0, 0.0, 0.000633333, 0.000633333], + [17.0, 17.0, 0.002332333, 2.33e-05, 0.0, 0.0, 0.0, 0.002332333, 0.002332333], + [18.0, 18.0, -0.000740333, -7.4e-06, 0.0, 0.0, 0.0, -0.000740333, -0.000740333], + [19.0, 19.0, 0.000566667, 5.67e-06, 0.0, 0.0, 0.0, 0.000566667, 0.000566667], + [20.0, 20.0, 0.002306667, 2.31e-05, 0.0, 0.0, 0.0, 0.002306667, 0.002306667], + [21.0, 21.0, 0.0006, 6e-06, 0.0, 0.0, 0.0, 0.0006, 0.0006], + [22.0, 22.0, 0.007484333, 7.48e-05, 0.0, 0.0, 0.0, 0.007484333, 0.007484333], + [23.0, 23.0, 0.034165333, 0.000341653, 0.0, 0.0, 0.0, 0.034165333, 0.034165333], + [24.0, 24.0, 0.015535333, 0.000155353, 0.0, 0.0, 0.0, 0.015535333, 0.015535333], + [25.0, 25.0, 0.017548667, 0.000175487, 0.0, 0.0, 0.0, 0.017548667, 0.017548667], + [26.0, 26.0, 0.007739333, 7.74e-05, 0.0, 0.0, 0.0, 0.007739333, 0.007739333], + [27.0, 27.0, 0.001166667, 1.17e-05, 0.0, 0.0, 0.0, 0.001166667, 0.001166667], + [28.0, 28.0, 0.002838, 2.84e-05, 0.0, 0.0, 0.0, 0.002838, 0.002838], + [29.0, 29.0, 0.008333333, 8.33e-05, 0.0, 0.0, 0.0, 0.008333333, 0.008333333], + [30.0, 30.0, 0.090333333, 0.000903333, 0.0, 0.0, 0.0, 0.090333333, 0.090333333], + [31.0, 31.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [32.0, 32.0, 0.019124333, 0.000191243, 0.0, 0.0, 0.0, 0.019124333, 0.019124333], + [33.0, 33.0, -0.018339, -0.00018339, 0.0, 0.0, 0.0, -0.018339, -0.018339], + [34.0, 34.0, 0.107100667, 0.001071007, 0.0, 0.0, 0.0, 0.107100667, 0.107100667], + [35.0, 35.0, 0.081759667, 0.000817597, 0.0, 0.0, 0.0, 0.081759667, 0.081759667], + [36.0, 36.0, 0.074532333, 0.000745323, 0.0, 0.0, 0.0, 0.074532333, 0.074532333], + [37.0, 37.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [38.0, 38.0, 0.019531, 0.00019531, 0.0, 0.0, 0.0, 0.019531, 0.019531], + [39.0, 39.0, 0.009567, 9.57e-05, 0.0, 0.0, 0.0, 0.009567, 0.009567], + [40.0, 40.0, 0.016669667, 0.000166697, 0.0, 0.0, 0.0, 0.016669667, 0.016669667], + [41.0, 41.0, 0.000260333, 2.6e-06, 0.0, 0.0, 0.0, 0.000260333, 0.000260333], + [42.0, 42.0, -0.093666667, -0.000936667, 0.0, 0.0, 0.0, -0.093666667, -0.093666667], + [43.0, 43.0, -0.121, -0.00121, 0.0, 0.0, 0.0, -0.121, -0.121], + [44.0, 44.0, 0.026635667, 0.000266357, 0.0, 0.0, 0.0, 0.026635667, 0.026635667], + [45.0, 45.0, 0.001526, 1.53e-05, 0.0, 0.0, 0.0, 0.001526, 0.001526], + [46.0, 46.0, 0.015, 0.00015, 0.0, 0.0, 0.0, 0.015, 0.015], + [47.0, 47.0, -0.195666667, -0.001956667, 0.0, 0.0, 0.0, -0.195666667, -0.195666667], + [48.0, 48.0, 0.002748, 2.75e-05, 0.0, 0.0, 0.0, 0.002748, 0.002748], + [49.0, 49.0, -0.0121, -0.000121, 0.0, 0.0, 0.0, -0.0121, -0.0121], + [50.0, 50.0, 0.0044, 4.4e-05, 0.0, 0.0, 0.0, 0.0044, 0.0044], + [51.0, 51.0, 0.001533333, 1.53e-05, 0.0, 0.0, 0.0, 0.001533333, 0.001533333], + [52.0, 52.0, -0.181333333, -0.001813333, 0.0, 0.0, 0.0, -0.181333333, -0.181333333], + [53.0, 53.0, 0.006189333, 6.19e-05, 0.0, 0.0, 0.0, 0.006189333, 0.006189333], + [54.0, 54.0, 0.0021, 2.1e-05, 0.0, 0.0, 0.0, 0.0021, 0.0021], + [55.0, 55.0, 0.0006, 6e-06, 0.0, 0.0, 0.0, 0.0006, 0.0006], + [56.0, 56.0, 0.008821, 8.82e-05, 0.0, 0.0, 0.0, 0.008821, 0.008821], + [57.0, 57.0, 0.023519333, 0.000235193, 0.0, 0.0, 0.0, 0.023519333, 0.023519333], + [58.0, 58.0, 0.000946667, 9.47e-06, 0.0, 0.0, 0.0, 0.000946667, 0.000946667], + [59.0, 59.0, -0.010598, -0.00010598, 0.0, 0.0, 0.0, -0.010598, -0.010598], + [60.0, 60.0, 0.031601, 0.00031601, 0.0, 0.0, 0.0, 0.031601, 0.031601], + [61.0, 61.0, 0.056173333, 0.000561733, 0.0, 0.0, 0.0, 0.056173333, 0.056173333], + [62.0, 62.0, 0.016211667, 0.000162117, 0.0, 0.0, 0.0, 0.016211667, 0.016211667], + [63.0, 63.0, 0.022671, 0.00022671, 0.0, 0.0, 0.0, 0.022671, 0.022671], + [64.0, 64.0, 0.006514333, 6.51e-05, 0.0, 0.0, 0.0, 0.006514333, 0.006514333], + [65.0, 65.0, 0.006666667, 6.67e-05, 0.0, 0.0, 0.0, 0.006666667, 0.006666667], + [66.0, 66.0, 0.036542333, 0.000365423, 0.0, 0.0, 0.0, 0.036542333, 0.036542333], + [67.0, 67.0, 0.036350333, 0.000363503, 0.0, 0.0, 0.0, 0.036350333, 0.036350333], + [68.0, 68.0, 0.044479333, 0.000444793, 0.0, 0.0, 0.0, 0.044479333, 0.044479333], + [69.0, 69.0, 0.037717667, 0.000377177, 0.0, 0.0, 0.0, 0.037717667, 0.037717667], + [70.0, 70.0, 0.015331333, 0.000153313, 0.0, 0.0, 0.0, 0.015331333, 0.015331333], + [71.0, 71.0, -0.017377333, -0.000173773, 0.0, 0.0, 0.0, -0.017377333, -0.017377333], + [72.0, 72.0, 0.524666667, 0.005246667, 0.0, 0.0, 0.0, 0.524666667, 0.524666667], + [73.0, 73.0, 0.038666667, 0.000386667, 0.0, 0.0, 0.0, 0.038666667, 0.038666667], + [74.0, 74.0, 0.009, 9e-05, 0.0, 0.0, 0.0, 0.009, 0.009], + [75.0, 75.0, 0.028793333, 0.000287933, 0.0, 0.0, 0.0, 0.028793333, 0.028793333], + [76.0, 76.0, 0.005333333, 5.33e-05, 0.0, 0.0, 0.0, 0.005333333, 0.005333333], + [77.0, 77.0, 0.001703, 1.7e-05, 0.0, 0.0, 0.0, 0.001703, 0.001703], + [78.0, 78.0, 0.007500333, 7.5e-05, 0.0, 0.0, 0.0, 0.007500333, 0.007500333], + [79.0, 79.0, 0.002896333, 2.9e-05, 0.0, 0.0, 0.0, 0.002896333, 0.002896333], + [80.0, 80.0, 0.0018, 1.8e-05, 0.0, 0.0, 0.0, 0.0018, 0.0018], + [81.0, 81.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [82.0, 82.0, 0.00476, 4.76e-05, 0.0, 0.0, 0.0, 0.00476, 0.00476], + [83.0, 83.0, -0.004191333, -4.19e-05, 0.0, 0.0, 0.0, -0.004191333, -0.004191333], + [84.0, 84.0, 0.00571, 5.71e-05, 0.0, 0.0, 0.0, 0.00571, 0.00571], + [85.0, 85.0, 0.003115667, 3.12e-05, 0.0, 0.0, 0.0, 0.003115667, 0.003115667], + [86.0, 86.0, -0.001128, -1.13e-05, 0.0, 0.0, 0.0, -0.001128, -0.001128], + [87.0, 87.0, 0.001928333, 1.93e-05, 0.0, 0.0, 0.0, 0.001928333, 0.001928333], + [88.0, 88.0, 0.000581333, 5.81e-06, 0.0, 0.0, 0.0, 0.000581333, 0.000581333], + [89.0, 89.0, 0.003095, 3.1e-05, 0.0, 0.0, 0.0, 0.003095, 0.003095], + [90.0, 90.0, 0.004434333, 4.43e-05, 0.0, 0.0, 0.0, 0.004434333, 0.004434333], + [91.0, 91.0, 0.004522333, 4.52e-05, 0.0, 0.0, 0.0, 0.004522333, 0.004522333], + [92.0, 92.0, 0.001226333, 1.23e-05, 0.0, 0.0, 0.0, 0.001226333, 0.001226333], + [93.0, 93.0, -0.007985667, -7.99e-05, 0.0, 0.0, 0.0, -0.007985667, -0.007985667], + [94.0, 94.0, 0.001045, 1.05e-05, 0.0, 0.0, 0.0, 0.001045, 0.001045], + [95.0, 95.0, 0.002198667, 2.2e-05, 0.0, 0.0, 0.0, 0.002198667, 0.002198667], + [96.0, 96.0, 0.001960667, 1.96e-05, 0.0, 0.0, 0.0, 0.001960667, 0.001960667], + [97.0, 97.0, -0.004037333, -4.04e-05, 0.0, 0.0, 0.0, -0.004037333, -0.004037333], + [98.0, 98.0, 0.000889667, 8.9e-06, 0.0, 0.0, 0.0, 0.000889667, 0.000889667], + [99.0, 99.0, 0.002322333, 2.32e-05, 0.0, 0.0, 0.0, 0.002322333, 0.002322333], + [100.0, 100.0, 0.001514667, 1.51e-05, 0.0, 0.0, 0.0, 0.001514667, 0.001514667], + [101.0, 101.0, -0.001014667, -1.01e-05, 0.0, 0.0, 0.0, -0.001014667, -0.001014667], + [102.0, 102.0, -0.000569333, -5.69e-06, 0.0, 0.0, 0.0, -0.000569333, -0.000569333], + [103.0, 103.0, 0.001540667, 1.54e-05, 0.0, 0.0, 0.0, 0.001540667, 0.001540667], + [104.0, 104.0, 0.001713667, 1.71e-05, 0.0, 0.0, 0.0, 0.001713667, 0.001713667], + [105.0, 105.0, 0.010341333, 0.000103413, 0.0, 0.0, 0.0, 0.010341333, 0.010341333], + [106.0, 106.0, 0.001034, 1.03e-05, 0.0, 0.0, 0.0, 0.001034, 0.001034], + [107.0, 107.0, 0.010526, 0.00010526, 0.0, 0.0, 0.0, 0.010526, 0.010526], + [108.0, 108.0, 0.016171, 0.00016171, 0.0, 0.0, 0.0, 0.016171, 0.016171], + [109.0, 109.0, 0.0017, 1.7e-05, 0.0, 0.0, 0.0, 0.0017, 0.0017], + [110.0, 110.0, -0.006899667, -6.9e-05, 0.0, 0.0, 0.0, -0.006899667, -0.006899667], + [111.0, 111.0, 0.002333333, 2.33e-05, 0.0, 0.0, 0.0, 0.002333333, 0.002333333], + [112.0, 112.0, 0.001, 1e-05, 0.0, 0.0, 0.0, 0.001, 0.001], + [113.0, 113.0, 0.002286667, 2.29e-05, 0.0, 0.0, 0.0, 0.002286667, 0.002286667], + [114.0, 114.0, -0.148, -0.00148, 0.0, 0.0, 0.0, -0.148, -0.148], + [115.0, 115.0, 0.001366667, 1.37e-05, 0.0, 0.0, 0.0, 0.001366667, 0.001366667], + [116.0, 116.0, 0.000533333, 5.33e-06, 0.0, 0.0, 0.0, 0.000533333, 0.000533333], + [117.0, 117.0, 0.000866667, 8.67e-06, 0.0, 0.0, 0.0, 0.000866667, 0.000866667], + [118.0, 118.0, 0.0019, 1.9e-05, 0.0, 0.0, 0.0, 0.0019, 0.0019], + [119.0, 119.0, 0.002525, 2.53e-05, 0.0, 0.0, 0.0, 0.002525, 0.002525], + [120.0, 120.0, -0.002066667, -2.07e-05, 0.0, 0.0, 0.0, -0.002066667, -0.002066667], + [121.0, 121.0, 0.0037, 3.7e-05, 0.0, 0.0, 0.0, 0.0037, 0.0037], + [122.0, 122.0, -0.002489333, -2.49e-05, 0.0, 0.0, 0.0, -0.002489333, -0.002489333], + [123.0, 123.0, -0.163, -0.00163, 0.0, 0.0, 0.0, -0.163, -0.163], + [124.0, 124.0, -0.000433333, -4.33e-06, 0.0, 0.0, 0.0, -0.000433333, -0.000433333], + [125.0, 125.0, -0.009256667, -9.26e-05, 0.0, 0.0, 0.0, -0.009256667, -0.009256667], + [126.0, 126.0, -0.001566667, -1.57e-05, 0.0, 0.0, 0.0, -0.001566667, -0.001566667], + [127.0, 127.0, -0.001365, -1.37e-05, 0.0, 0.0, 0.0, -0.001365, -0.001365], + [128.0, 128.0, 0.005666667, 5.67e-05, 0.0, 0.0, 0.0, 0.005666667, 0.005666667], + [129.0, 129.0, 0.001833333, 1.83e-05, 0.0, 0.0, 0.0, 0.001833333, 0.001833333], + [130.0, 130.0, 0.000166667, 1.67e-06, 0.0, 0.0, 0.0, 0.000166667, 0.000166667], + [131.0, 131.0, 0.000252667, 2.53e-06, 0.0, 0.0, 0.0, 0.000252667, 0.000252667], + [132.0, 132.0, 0.003044667, 3.04e-05, 0.0, 0.0, 0.0, 0.003044667, 0.003044667], + [133.0, 133.0, 0.004182667, 4.18e-05, 0.0, 0.0, 0.0, 0.004182667, 0.004182667], + [134.0, 134.0, 0.001166667, 1.17e-05, 0.0, 0.0, 0.0, 0.001166667, 0.001166667], + [135.0, 135.0, 0.006259667, 6.26e-05, 0.0, 0.0, 0.0, 0.006259667, 0.006259667], + [136.0, 136.0, 0.0051, 5.1e-05, 0.0, 0.0, 0.0, 0.0051, 0.0051], + [137.0, 137.0, 0.001066667, 1.07e-05, 0.0, 0.0, 0.0, 0.001066667, 0.001066667], + [138.0, 138.0, 0.000204, 2.04e-06, 0.0, 0.0, 0.0, 0.000204, 0.000204], + [139.0, 139.0, -0.004076, -4.08e-05, 0.0, 0.0, 0.0, -0.004076, -0.004076], + [140.0, 140.0, -0.001299667, -1.3e-05, 0.0, 0.0, 0.0, -0.001299667, -0.001299667], + [141.0, 141.0, -0.003872, -3.87e-05, 0.0, 0.0, 0.0, -0.003872, -0.003872], + [142.0, 142.0, 0.004060333, 4.06e-05, 0.0, 0.0, 0.0, 0.004060333, 0.004060333], + [143.0, 143.0, -0.008910333, -8.91e-05, 0.0, 0.0, 0.0, -0.008910333, -0.008910333], + [144.0, 144.0, -0.000287, -2.87e-06, 0.0, 0.0, 0.0, -0.000287, -0.000287], + [145.0, 145.0, 0.006719333, 6.72e-05, 0.0, 0.0, 0.0, 0.006719333, 0.006719333], + [146.0, 146.0, -0.004702667, -4.7e-05, 0.0, 0.0, 0.0, -0.004702667, 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457.0, 0.002, 2e-05, 0.0, 0.0, 0.0, 0.002, 0.002], + [458.0, 458.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [459.0, 459.0, 0.001395667, 1.4e-05, 0.0, 0.0, 0.0, 0.001395667, 0.001395667], + [460.0, 460.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [461.0, 461.0, -0.016939667, -0.000169397, 0.0, 0.0, 0.0, -0.016939667, -0.016939667], + [462.0, 462.0, 0.000971, 9.71e-06, 0.0, 0.0, 0.0, 0.000971, 0.000971], + [463.0, 463.0, 0.005468333, 5.47e-05, 0.0, 0.0, 0.0, 0.005468333, 0.005468333], + [464.0, 464.0, -0.000445, -4.45e-06, 0.0, 0.0, 0.0, -0.000445, -0.000445], + [465.0, 465.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [466.0, 466.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [467.0, 467.0, 0.00022, 2.2e-06, 0.0, 0.0, 0.0, 0.00022, 0.00022], + [468.0, 468.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [469.0, 469.0, 0.001345, 1.35e-05, 0.0, 0.0, 0.0, 0.001345, 0.001345], + [470.0, 470.0, -0.006583667, -6.58e-05, 0.0, 0.0, 0.0, -0.006583667, -0.006583667], + [471.0, 471.0, 0.003801333, 3.8e-05, 0.0, 0.0, 0.0, 0.003801333, 0.003801333], + [472.0, 472.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [473.0, 473.0, 0.000517, 5.17e-06, 0.0, 0.0, 0.0, 0.000517, 0.000517], + [474.0, 474.0, 0.005309, 5.31e-05, 0.0, 0.0, 0.0, 0.005309, 0.005309], + [475.0, 475.0, -0.015929333, -0.000159293, 0.0, 0.0, 0.0, -0.015929333, -0.015929333], + [476.0, 476.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [477.0, 477.0, 0.003926333, 3.93e-05, 0.0, 0.0, 0.0, 0.003926333, 0.003926333], + [478.0, 478.0, 0.002044, 2.04e-05, 0.0, 0.0, 0.0, 0.002044, 0.002044], + [479.0, 479.0, -0.003583, -3.58e-05, 0.0, 0.0, 0.0, -0.003583, -0.003583], + [480.0, 480.0, -0.008388667, -8.39e-05, 0.0, 0.0, 0.0, -0.008388667, -0.008388667], + [481.0, 481.0, 0.000987, 9.87e-06, 0.0, 0.0, 0.0, 0.000987, 0.000987], + [482.0, 482.0, 0.001138, 1.14e-05, 0.0, 0.0, 0.0, 0.001138, 0.001138], + [483.0, 483.0, -0.000517667, -5.18e-06, 0.0, 0.0, 0.0, -0.000517667, -0.000517667], + [484.0, 484.0, 0.000857, 8.57e-06, 0.0, 0.0, 0.0, 0.000857, 0.000857], + [485.0, 485.0, -0.012213, -0.00012213, 0.0, 0.0, 0.0, -0.012213, -0.012213], + [486.0, 486.0, 0.001971, 1.97e-05, 0.0, 0.0, 0.0, 0.001971, 0.001971], + [487.0, 487.0, -0.003363, -3.36e-05, 0.0, 0.0, 0.0, -0.003363, -0.003363], + [488.0, 488.0, 0.000744667, 7.45e-06, 0.0, 0.0, 0.0, 0.000744667, 0.000744667], + [489.0, 489.0, 0.003361, 3.36e-05, 0.0, 0.0, 0.0, 0.003361, 0.003361], + [490.0, 490.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [491.0, 491.0, 0.001970667, 1.97e-05, 0.0, 0.0, 0.0, 0.001970667, 0.001970667], + [492.0, 492.0, -0.001553667, -1.55e-05, 0.0, 0.0, 0.0, -0.001553667, -0.001553667], + [493.0, 493.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [494.0, 494.0, 0.002171667, 2.17e-05, 0.0, 0.0, 0.0, 0.002171667, 0.002171667], + [495.0, 495.0, 0.000681, 6.81e-06, 0.0, 0.0, 0.0, 0.000681, 0.000681], + [496.0, 496.0, 0.025579333, 0.000255793, 0.0, 0.0, 0.0, 0.025579333, 0.025579333], + [497.0, 497.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [498.0, 498.0, -0.001396667, -1.4e-05, 0.0, 0.0, 0.0, -0.001396667, -0.001396667], + [499.0, 499.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [500.0, 500.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [501.0, 501.0, 1.33e-06, 1.33e-08, 0.0, 0.0, 0.0, 1.33e-06, 1.33e-06], + [502.0, 502.0, 0.001276667, 1.28e-05, 0.0, 0.0, 0.0, 0.001276667, 0.001276667], + [503.0, 503.0, 0.000752333, 7.52e-06, 0.0, 0.0, 0.0, 0.000752333, 0.000752333], + [504.0, 504.0, -0.007499667, -7.5e-05, 0.0, 0.0, 0.0, -0.007499667, -0.007499667], + [505.0, 505.0, 0.001766667, 1.77e-05, 0.0, 0.0, 0.0, 0.001766667, 0.001766667], + [506.0, 506.0, 0.001148667, 1.15e-05, 0.0, 0.0, 0.0, 0.001148667, 0.001148667], + [507.0, 507.0, 0.017846, 0.00017846, 0.0, 0.0, 0.0, 0.017846, 0.017846], + [508.0, 508.0, 0.008606, 8.61e-05, 0.0, 0.0, 0.0, 0.008606, 0.008606], + [509.0, 509.0, 0.019756, 0.00019756, 0.0, 0.0, 0.0, 0.019756, 0.019756], + [510.0, 510.0, -0.017048667, -0.000170487, 0.0, 0.0, 0.0, -0.017048667, -0.017048667], + [511.0, 511.0, 0.050497667, 0.000504977, 0.0, 0.0, 0.0, 0.050497667, 0.050497667], + [512.0, 512.0, 0.047415667, 0.000474157, 0.0, 0.0, 0.0, 0.047415667, 0.047415667], + [513.0, 513.0, 0.002659333, 2.66e-05, 0.0, 0.0, 0.0, 0.002659333, 0.002659333], + [514.0, 514.0, 0.005978333, 5.98e-05, 0.0, 0.0, 0.0, 0.005978333, 0.005978333], + [515.0, 515.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [516.0, 516.0, 0.009586333, 9.59e-05, 0.0, 0.0, 0.0, 0.009586333, 0.009586333], + [517.0, 517.0, 0.001947667, 1.95e-05, 0.0, 0.0, 0.0, 0.001947667, 0.001947667], + [518.0, 518.0, -0.009107333, -9.11e-05, 0.0, 0.0, 0.0, -0.009107333, -0.009107333], + [519.0, 519.0, 0.002887333, 2.89e-05, 0.0, 0.0, 0.0, 0.002887333, 0.002887333], + [520.0, 520.0, 0.005236, 5.24e-05, 0.0, 0.0, 0.0, 0.005236, 0.005236], + [521.0, 521.0, 0.00307, 3.07e-05, 0.0, 0.0, 0.0, 0.00307, 0.00307], + [522.0, 522.0, -0.000959333, -9.59e-06, 0.0, 0.0, 0.0, -0.000959333, -0.000959333], + [523.0, 523.0, 0.005016667, 5.02e-05, 0.0, 0.0, 0.0, 0.005016667, 0.005016667], + [524.0, 524.0, 0.012321333, 0.000123213, 0.0, 0.0, 0.0, 0.012321333, 0.012321333], + [525.0, 525.0, 0.003456, 3.46e-05, 0.0, 0.0, 0.0, 0.003456, 0.003456], + [526.0, 526.0, 0.006206333, 6.21e-05, 0.0, 0.0, 0.0, 0.006206333, 0.006206333], + [527.0, 527.0, -0.03656, -0.0003656, 0.0, 0.0, 0.0, -0.03656, -0.03656], + [528.0, 528.0, 0.001296, 1.3e-05, 0.0, 0.0, 0.0, 0.001296, 0.001296], + [529.0, 529.0, 0.003147667, 3.15e-05, 0.0, 0.0, 0.0, 0.003147667, 0.003147667], + [530.0, 530.0, 0.003143, 3.14e-05, 0.0, 0.0, 0.0, 0.003143, 0.003143], + [531.0, 531.0, 0.005816333, 5.82e-05, 0.0, 0.0, 0.0, 0.005816333, 0.005816333], + [532.0, 532.0, -0.000495, -4.95e-06, 0.0, 0.0, 0.0, -0.000495, -0.000495], + [533.0, 533.0, -0.000610333, -6.1e-06, 0.0, 0.0, 0.0, -0.000610333, -0.000610333]]) + + self.real_params = True + super().__init__(*args, **kwargs) diff --git a/powergrid_case/distribution/__init__.py b/powergrid_case/distribution/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..d49122e667c62e7c4352ed1a7dcc2c9c61c1d56f --- /dev/null +++ b/powergrid_case/distribution/__init__.py @@ -0,0 +1,17 @@ +"""Distribution grid case data.""" + +from .Case33bw import Case33bw +from .Case118zh import Case118zh +from .Case123 import Case123 +from .Case141 import Case141 +from .Case533mt_hi import Case533mt_hi +from .Case533mt_lo import Case533mt_lo + +__all__ = [ + "Case33bw", + "Case118zh", + "Case123", + "Case141", + "Case533mt_hi", + "Case533mt_lo", +] diff --git a/powergrid_case/transmission/Case118.py b/powergrid_case/transmission/Case118.py new file mode 100644 index 0000000000000000000000000000000000000000..00de45ad6b9b5817f3ec1272e21c25a41696376d --- /dev/null +++ b/powergrid_case/transmission/Case118.py @@ -0,0 +1,535 @@ +"""IEEE 118-bus system (MATPOWER case118) + +Topology and power-flow data (nodes / lines / generator Pg–Qg–Vg) follow +MATPOWER `data/case118.m` (bundled as `source_mfile/case118.m`). + +UC-style economic columns (`type`, `mc_*`, `p_max`/`p_min`, ramps, …) are +preserved from the previous PowerZoo Case118 SCUC-style table, keyed by +`bus_id` (54 generators; unique buses). + +Nodes / lines include full MATPOWER fields so `cal_pf_trans.run_acpf` and +`run_dcpf` work on `Case118().init()`. + +Base MVA: 100 MVA +""" +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case118(ClearCase): + GRID_TYPE = "transmission" + BUS_COUNT = 118 + VOLTAGE_LEVEL = "HV" + SOURCE = "MATPOWER" + DESCRIPTION = "IEEE 118-bus test system" + + def __init__(self, *args, **kwargs): + self.baseMVA = 100 + self.baseKV = 138.0 + + self.nodes = DataFrame( + ['id', 'type', 'Pd', 'Qd', 'Gs', 'Bs', 'Vm', 'Va', 'baseKV', 'Vmax', 'Vmin'], + [ + [1, 2, 51, 27, 0, 0, 0.955, 10.67, 138, 1.06, 0.94], + [2, 1, 20, 9, 0, 0, 0.971, 11.22, 138, 1.06, 0.94], + [3, 1, 39, 10, 0, 0, 0.968, 11.56, 138, 1.06, 0.94], + [4, 2, 39, 12, 0, 0, 0.998, 15.28, 138, 1.06, 0.94], + [5, 1, 0, 0, 0, -40, 1.002, 15.73, 138, 1.06, 0.94], + [6, 2, 52, 22, 0, 0, 0.99, 13, 138, 1.06, 0.94], + [7, 1, 19, 2, 0, 0, 0.989, 12.56, 138, 1.06, 0.94], + [8, 2, 28, 0, 0, 0, 1.015, 20.77, 345, 1.06, 0.94], + [9, 1, 0, 0, 0, 0, 1.043, 28.02, 345, 1.06, 0.94], + [10, 2, 0, 0, 0, 0, 1.05, 35.61, 345, 1.06, 0.94], + [11, 1, 70, 23, 0, 0, 0.985, 12.72, 138, 1.06, 0.94], + [12, 2, 47, 10, 0, 0, 0.99, 12.2, 138, 1.06, 0.94], + [13, 1, 34, 16, 0, 0, 0.968, 11.35, 138, 1.06, 0.94], + [14, 1, 14, 1, 0, 0, 0.984, 11.5, 138, 1.06, 0.94], + [15, 2, 90, 30, 0, 0, 0.97, 11.23, 138, 1.06, 0.94], + [16, 1, 25, 10, 0, 0, 0.984, 11.91, 138, 1.06, 0.94], + [17, 1, 11, 3, 0, 0, 0.995, 13.74, 138, 1.06, 0.94], + [18, 2, 60, 34, 0, 0, 0.973, 11.53, 138, 1.06, 0.94], + [19, 2, 45, 25, 0, 0, 0.963, 11.05, 138, 1.06, 0.94], + [20, 1, 18, 3, 0, 0, 0.958, 11.93, 138, 1.06, 0.94], + [21, 1, 14, 8, 0, 0, 0.959, 13.52, 138, 1.06, 0.94], + [22, 1, 10, 5, 0, 0, 0.97, 16.08, 138, 1.06, 0.94], + [23, 1, 7, 3, 0, 0, 1, 21, 138, 1.06, 0.94], + [24, 2, 13, 0, 0, 0, 0.992, 20.89, 138, 1.06, 0.94], + [25, 2, 0, 0, 0, 0, 1.05, 27.93, 138, 1.06, 0.94], + [26, 2, 0, 0, 0, 0, 1.015, 29.71, 345, 1.06, 0.94], + [27, 2, 71, 13, 0, 0, 0.968, 15.35, 138, 1.06, 0.94], + [28, 1, 17, 7, 0, 0, 0.962, 13.62, 138, 1.06, 0.94], + [29, 1, 24, 4, 0, 0, 0.963, 12.63, 138, 1.06, 0.94], + [30, 1, 0, 0, 0, 0, 0.968, 18.79, 345, 1.06, 0.94], + [31, 2, 43, 27, 0, 0, 0.967, 12.75, 138, 1.06, 0.94], + [32, 2, 59, 23, 0, 0, 0.964, 14.8, 138, 1.06, 0.94], + [33, 1, 23, 9, 0, 0, 0.972, 10.63, 138, 1.06, 0.94], + [34, 2, 59, 26, 0, 14, 0.986, 11.3, 138, 1.06, 0.94], + [35, 1, 33, 9, 0, 0, 0.981, 10.87, 138, 1.06, 0.94], + [36, 2, 31, 17, 0, 0, 0.98, 10.87, 138, 1.06, 0.94], + [37, 1, 0, 0, 0, -25, 0.992, 11.77, 138, 1.06, 0.94], + [38, 1, 0, 0, 0, 0, 0.962, 16.91, 345, 1.06, 0.94], + [39, 1, 27, 11, 0, 0, 0.97, 8.41, 138, 1.06, 0.94], + [40, 2, 66, 23, 0, 0, 0.97, 7.35, 138, 1.06, 0.94], + [41, 1, 37, 10, 0, 0, 0.967, 6.92, 138, 1.06, 0.94], + [42, 2, 96, 23, 0, 0, 0.985, 8.53, 138, 1.06, 0.94], + [43, 1, 18, 7, 0, 0, 0.978, 11.28, 138, 1.06, 0.94], + [44, 1, 16, 8, 0, 10, 0.985, 13.82, 138, 1.06, 0.94], + [45, 1, 53, 22, 0, 10, 0.987, 15.67, 138, 1.06, 0.94], + [46, 2, 28, 10, 0, 10, 1.005, 18.49, 138, 1.06, 0.94], + [47, 1, 34, 0, 0, 0, 1.017, 20.73, 138, 1.06, 0.94], + [48, 1, 20, 11, 0, 15, 1.021, 19.93, 138, 1.06, 0.94], + [49, 2, 87, 30, 0, 0, 1.025, 20.94, 138, 1.06, 0.94], + [50, 1, 17, 4, 0, 0, 1.001, 18.9, 138, 1.06, 0.94], + [51, 1, 17, 8, 0, 0, 0.967, 16.28, 138, 1.06, 0.94], + [52, 1, 18, 5, 0, 0, 0.957, 15.32, 138, 1.06, 0.94], + [53, 1, 23, 11, 0, 0, 0.946, 14.35, 138, 1.06, 0.94], + [54, 2, 113, 32, 0, 0, 0.955, 15.26, 138, 1.06, 0.94], + [55, 2, 63, 22, 0, 0, 0.952, 14.97, 138, 1.06, 0.94], + [56, 2, 84, 18, 0, 0, 0.954, 15.16, 138, 1.06, 0.94], + [57, 1, 12, 3, 0, 0, 0.971, 16.36, 138, 1.06, 0.94], + [58, 1, 12, 3, 0, 0, 0.959, 15.51, 138, 1.06, 0.94], + [59, 2, 277, 113, 0, 0, 0.985, 19.37, 138, 1.06, 0.94], + [60, 1, 78, 3, 0, 0, 0.993, 23.15, 138, 1.06, 0.94], + [61, 2, 0, 0, 0, 0, 0.995, 24.04, 138, 1.06, 0.94], + [62, 2, 77, 14, 0, 0, 0.998, 23.43, 138, 1.06, 0.94], + [63, 1, 0, 0, 0, 0, 0.969, 22.75, 345, 1.06, 0.94], + [64, 1, 0, 0, 0, 0, 0.984, 24.52, 345, 1.06, 0.94], + [65, 2, 0, 0, 0, 0, 1.005, 27.65, 345, 1.06, 0.94], + [66, 2, 39, 18, 0, 0, 1.05, 27.48, 138, 1.06, 0.94], + [67, 1, 28, 7, 0, 0, 1.02, 24.84, 138, 1.06, 0.94], + [68, 1, 0, 0, 0, 0, 1.003, 27.55, 345, 1.06, 0.94], + [69, 3, 0, 0, 0, 0, 1.035, 30, 138, 1.06, 0.94], + [70, 2, 66, 20, 0, 0, 0.984, 22.58, 138, 1.06, 0.94], + [71, 1, 0, 0, 0, 0, 0.987, 22.15, 138, 1.06, 0.94], + [72, 2, 12, 0, 0, 0, 0.98, 20.98, 138, 1.06, 0.94], + [73, 2, 6, 0, 0, 0, 0.991, 21.94, 138, 1.06, 0.94], + [74, 2, 68, 27, 0, 12, 0.958, 21.64, 138, 1.06, 0.94], + [75, 1, 47, 11, 0, 0, 0.967, 22.91, 138, 1.06, 0.94], + [76, 2, 68, 36, 0, 0, 0.943, 21.77, 138, 1.06, 0.94], + [77, 2, 61, 28, 0, 0, 1.006, 26.72, 138, 1.06, 0.94], + [78, 1, 71, 26, 0, 0, 1.003, 26.42, 138, 1.06, 0.94], + [79, 1, 39, 32, 0, 20, 1.009, 26.72, 138, 1.06, 0.94], + [80, 2, 130, 26, 0, 0, 1.04, 28.96, 138, 1.06, 0.94], + [81, 1, 0, 0, 0, 0, 0.997, 28.1, 345, 1.06, 0.94], + [82, 1, 54, 27, 0, 20, 0.989, 27.24, 138, 1.06, 0.94], + [83, 1, 20, 10, 0, 10, 0.985, 28.42, 138, 1.06, 0.94], + [84, 1, 11, 7, 0, 0, 0.98, 30.95, 138, 1.06, 0.94], + [85, 2, 24, 15, 0, 0, 0.985, 32.51, 138, 1.06, 0.94], + [86, 1, 21, 10, 0, 0, 0.987, 31.14, 138, 1.06, 0.94], + [87, 2, 0, 0, 0, 0, 1.015, 31.4, 161, 1.06, 0.94], + [88, 1, 48, 10, 0, 0, 0.987, 35.64, 138, 1.06, 0.94], + [89, 2, 0, 0, 0, 0, 1.005, 39.69, 138, 1.06, 0.94], + [90, 2, 163, 42, 0, 0, 0.985, 33.29, 138, 1.06, 0.94], + [91, 2, 10, 0, 0, 0, 0.98, 33.31, 138, 1.06, 0.94], + [92, 2, 65, 10, 0, 0, 0.993, 33.8, 138, 1.06, 0.94], + [93, 1, 12, 7, 0, 0, 0.987, 30.79, 138, 1.06, 0.94], + [94, 1, 30, 16, 0, 0, 0.991, 28.64, 138, 1.06, 0.94], + [95, 1, 42, 31, 0, 0, 0.981, 27.67, 138, 1.06, 0.94], + [96, 1, 38, 15, 0, 0, 0.993, 27.51, 138, 1.06, 0.94], + [97, 1, 15, 9, 0, 0, 1.011, 27.88, 138, 1.06, 0.94], + [98, 1, 34, 8, 0, 0, 1.024, 27.4, 138, 1.06, 0.94], + [99, 2, 42, 0, 0, 0, 1.01, 27.04, 138, 1.06, 0.94], + [100, 2, 37, 18, 0, 0, 1.017, 28.03, 138, 1.06, 0.94], + [101, 1, 22, 15, 0, 0, 0.993, 29.61, 138, 1.06, 0.94], + [102, 1, 5, 3, 0, 0, 0.991, 32.3, 138, 1.06, 0.94], + [103, 2, 23, 16, 0, 0, 1.001, 24.44, 138, 1.06, 0.94], + [104, 2, 38, 25, 0, 0, 0.971, 21.69, 138, 1.06, 0.94], + [105, 2, 31, 26, 0, 20, 0.965, 20.57, 138, 1.06, 0.94], + [106, 1, 43, 16, 0, 0, 0.962, 20.32, 138, 1.06, 0.94], + [107, 2, 50, 12, 0, 6, 0.952, 17.53, 138, 1.06, 0.94], + [108, 1, 2, 1, 0, 0, 0.967, 19.38, 138, 1.06, 0.94], + [109, 1, 8, 3, 0, 0, 0.967, 18.93, 138, 1.06, 0.94], + [110, 2, 39, 30, 0, 6, 0.973, 18.09, 138, 1.06, 0.94], + [111, 2, 0, 0, 0, 0, 0.98, 19.74, 138, 1.06, 0.94], + [112, 2, 68, 13, 0, 0, 0.975, 14.99, 138, 1.06, 0.94], + [113, 2, 6, 0, 0, 0, 0.993, 13.74, 138, 1.06, 0.94], + [114, 1, 8, 3, 0, 0, 0.96, 14.46, 138, 1.06, 0.94], + [115, 1, 22, 7, 0, 0, 0.96, 14.46, 138, 1.06, 0.94], + [116, 2, 184, 0, 0, 0, 1.005, 27.12, 138, 1.06, 0.94], + [117, 1, 20, 8, 0, 0, 0.974, 10.67, 138, 1.06, 0.94], + [118, 1, 33, 15, 0, 0, 0.949, 21.92, 138, 1.06, 0.94] + ]) + + self.units = DataFrame( + ['id', 'bus_id', 'Pg', 'Qg', 'Qmax', 'Qmin', 'Vg', 'mBase', 'status', + 'Pmax', 'Pmin', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min', + 'type', 'ramp_up', 'ramp_down', 'init_start_up_cost', 'keep_time', + 'init_power', 'init_state', 'min_up_time', 'min_down_time', 'init_no_load_cost'], + [ + [1, 1, 0, 0, 15, -5, 0.955, 100, 1, 100, 0, 0.030864, -2.335, 70, 90, 18, 'coal', 0.7, 0.7, 14167, -96, 0, 0, 4, 4, 941.73], + [2, 4, 0, 0, 300, -300, 0.998, 100, 1, 100, 0, 0.029537, -2.284239, 70, 92, 18, 'coal', 0.7, 0.7, 11377, -96, 0, 0, 4, 4, 962.66], + [3, 6, 0, 0, 50, -13, 0.99, 100, 1, 100, 0, 0.043824, -4.543579, 138, 95, 19, 'gas', 0.7, 0.7, 9153, -96, 0, 0, 1, 1, 1902.08], + [4, 8, 0, 0, 300, -300, 1.015, 100, 1, 100, 0, 0.042916, -4.49625, 138, 96, 19, 'gas', 0.7, 0.7, 8777, -96, 0, 0, 1, 1, 1922.1], + [5, 10, 450, 0, 200, -147, 1.05, 100, 1, 550, 0, 0.000826, -0.382091, 64, 550, 110, 'coal', 0.7, 0.7, 11948, 96, 110, 1, 4, 4, 5095.02], + [6, 12, 85, 0, 120, -35, 0.99, 100, 1, 185, 0, 0.00303, -0.629467, 33, 169, 34, 'nuclear', 0.7, 0.7, 25094, 96, 169, 1, 96, 96, 794.84], + [7, 15, 0, 0, 30, -10, 0.97, 100, 1, 100, 0, 0.046728, -4.691739, 139, 92, 18, 'gas', 0.7, 0.7, 9745, -96, 0, 0, 1, 1, 1860.41], + [8, 18, 0, 0, 50, -16, 0.973, 100, 1, 100, 0, 0.028905, -2.259677, 70, 93, 19, 'coal', 0.6999, 0.6999, 11402, 96, 93, 1, 4, 4, 973.12], + [9, 19, 0, 0, 24, -8, 0.962, 100, 1, 100, 0, 0.032283, -2.388068, 70, 88, 18, 'coal', 0.7, 0.7, 14277, 96, 88, 1, 4, 4, 920.8], + [10, 24, 0, 0, 300, -300, 0.992, 100, 1, 100, 0, 0.029537, -2.284239, 70, 92, 18, 'coal', 0.7, 0.7, 15093, 96, 92, 1, 4, 4, 962.66], + [11, 25, 220, 0, 140, -47, 1.05, 100, 1, 320, 0, 0.000883, -0.339872, 32, 313, 63, 'nuclear', 0.7, 0.7, 49408, 96, 313, 1, 96, 96, 1409.49], + [12, 26, 314, 0, 1000, -1000, 1.015, 100, 1, 414, 0, 0.002319, -1.045133, 130, 413, 83, 'gas', 0.7, 0.7, 8867, -96, 0, 0, 1, 1, 7608.24], + [13, 27, 0, 0, 300, -300, 0.968, 100, 1, 100, 0, 0.032283, -2.388068, 70, 88, 18, 'coal', 0.7, 0.7, 13902, 96, 88, 1, 4, 4, 920.8], + [14, 31, 7, 0, 300, -300, 0.967, 100, 1, 107, 0, 0.0352, -4.072075, 138, 106, 21, 'gas', 0.7, 0.7, 9954, -96, 0, 0, 1, 1, 2122.32], + [15, 32, 0, 0, 42, -14, 0.963, 100, 1, 100, 0, 0.032283, -2.388068, 70, 88, 18, 'coal', 0.7001, 0.7001, 11115, 96, 88, 1, 4, 4, 920.8], + [16, 34, 0, 0, 24, -8, 0.984, 100, 1, 100, 0, 0.029537, -2.284239, 70, 92, 18, 'coal', 0.7, 0.7, 11897, -96, 0, 0, 4, 4, 962.66], + [17, 36, 0, 0, 24, -8, 0.98, 100, 1, 100, 0, 0.046728, -4.691739, 139, 92, 18, 'gas', 0.7001, 0.7001, 9925, 96, 92, 1, 1, 1, 1860.41], + [18, 40, 0, 0, 300, -300, 0.97, 100, 1, 100, 0, 0.044761, -4.591915, 138, 94, 19, 'gas', 0.7, 0.7, 8680, -96, 0, 0, 1, 1, 1882.06], + [19, 42, 0, 0, 300, -300, 0.985, 100, 1, 100, 0, 0.043824, -4.543579, 138, 95, 19, 'gas', 0.7, 0.7, 7309, 96, 95, 1, 1, 1, 1902.08], + [20, 46, 19, 0, 100, -100, 1.005, 100, 1, 119, 0, 0.017955, -1.780932, 69, 118, 24, 'coal', 0.7, 0.7, 17685, 96, 24, 1, 4, 4, 1211.11], + [21, 49, 204, 0, 210, -85, 1.025, 100, 1, 304, 0, 0.000949, -0.352252, 32, 302, 60, 'nuclear', 0.7, 0.7, 53638, 96, 302, 1, 96, 96, 1359.96], + [22, 54, 48, 0, 300, -300, 0.955, 100, 1, 148, 0, 0.012056, -1.459375, 69, 144, 29, 'coal', 0.7, 0.7, 12008, -96, 0, 0, 4, 4, 1477.97], + [23, 55, 0, 0, 23, -8, 0.952, 100, 1, 100, 0, 0.042916, -4.49625, 138, 96, 19, 'gas', 0.7, 0.7, 7920, -96, 0, 0, 1, 1, 1922.1], + [24, 56, 0, 0, 15, -8, 0.954, 100, 1, 100, 0, 0.029537, -2.284239, 70, 92, 18, 'coal', 0.7, 0.7, 14251, -96, 0, 0, 4, 4, 962.66], + [25, 59, 155, 0, 180, -60, 0.985, 100, 1, 255, 0, 0.004032, -0.843976, 68, 249, 50, 'coal', 0.7, 0.7, 18429, 96, 249, 1, 4, 4, 2505.85], + [26, 61, 160, 0, 300, -100, 0.995, 100, 1, 260, 0, 0.003815, -0.820898, 68, 256, 51, 'coal', 0.7, 0.7, 18041, 96, 256, 1, 4, 4, 2576.3], + [27, 62, 0, 0, 20, -20, 0.998, 100, 1, 100, 0, 0.042916, -4.49625, 138, 96, 19, 'gas', 0.7, 0.7, 5163, -96, 0, 0, 1, 1, 1922.1], + [28, 65, 391, 0, 200, -67, 1.005, 100, 1, 491, 0, 0.001641, -0.879104, 128, 491, 98, 'gas', 0.7, 0.7, 8340, 96, 98, 1, 1, 1, 8848.75], + [29, 66, 392, 0, 200, -67, 1.05, 100, 1, 492, 0, 0.001033, -0.427134, 65, 492, 98, 'coal', 0.7, 0.7, 10019, 96, 98, 1, 4, 4, 4656.12], + [30, 69, 516.4, 0, 300, -300, 1.035, 100, 1, 805.2, 0, 0.000134, -0.132149, 30, 805, 161, 'nuclear', 0.7, 0.7, 105237, -96, 0, 0, 96, 96, 3303.05], + [31, 70, 0, 0, 32, -10, 0.984, 100, 1, 100, 0, 0.028905, -2.259677, 70, 93, 19, 'coal', 0.7, 0.7, 14265, -96, 0, 0, 4, 4, 973.12], + [32, 72, 0, 0, 100, -100, 0.98, 100, 1, 100, 0, 0.028293, -2.235638, 70, 94, 19, 'coal', 0.7, 0.7, 11281, 96, 94, 1, 4, 4, 983.58], + [33, 73, 0, 0, 100, -100, 0.991, 100, 1, 100, 0, 0.035431, -2.501786, 70, 84, 17, 'coal', 0.7, 0.7, 12609, -96, 0, 0, 4, 4, 878.95], + [34, 74, 0, 0, 9, -6, 0.958, 100, 1, 100, 0, 0.047761, -4.743297, 139, 91, 18, 'gas', 0.7, 0.7, 7543, 96, 85, 1, 1, 1, 1840.19], + [35, 76, 0, 0, 23, -8, 0.943, 100, 1, 100, 0, 0.028293, -2.235638, 70, 94, 19, 'coal', 0.7, 0.7, 12383, -96, 0, 0, 4, 4, 983.58], + [36, 77, 0, 0, 70, -20, 1.006, 100, 1, 100, 0, 0.029537, -2.284239, 70, 92, 18, 'coal', 0.7, 0.7, 11580, -96, 0, 0, 4, 4, 962.66], + [37, 80, 477, 0, 280, -165, 1.04, 100, 1, 577, 0, 0.000751, -0.364211, 64, 577, 115, 'coal', 0.7, 0.7, 11367, 96, 115, 1, 4, 4, 5345.14], + [38, 85, 0, 0, 23, -8, 0.985, 100, 1, 100, 0, 0.029537, -2.284239, 70, 92, 18, 'coal', 0.7, 0.7, 11322, 96, 92, 1, 4, 4, 962.66], + [39, 87, 4, 0, 1000, -100, 1.015, 100, 1, 104, 0, 0.025508, -2.122727, 70, 99, 20, 'coal', 0.7, 0.7, 10239, -96, 0, 0, 4, 4, 1035.9], + [40, 89, 607, 0, 300, -210, 1.005, 100, 1, 707, 0, 0.000518, -0.302374, 62, 695, 139, 'coal', 0.7, 0.7, 18192, 96, 139, 1, 4, 4, 6160.25], + [41, 90, 0, 0, 300, -300, 0.985, 100, 1, 100, 0, 0.045729, -4.64129, 139, 93, 19, 'gas', 0.6999, 0.6999, 7559, -96, 0, 0, 1, 1, 1880.64], + [42, 91, 0, 0, 100, -100, 0.98, 100, 1, 100, 0, 0.028905, -2.259677, 70, 93, 19, 'coal', 0.7, 0.7, 13464, 96, 93, 1, 4, 4, 973.12], + [43, 92, 0, 0, 9, -3, 0.99, 100, 1, 100, 0, 0.028293, -2.235638, 70, 94, 19, 'coal', 0.7, 0.7, 13218, 96, 94, 1, 4, 4, 983.58], + [44, 99, 0, 0, 100, -100, 1.01, 100, 1, 100, 0, 0.028293, -2.235638, 70, 94, 19, 'coal', 0.7, 0.7, 10277, -96, 0, 0, 4, 4, 983.58], + [45, 100, 252, 0, 155, -50, 1.017, 100, 1, 352, 0, 0.000698, -0.302216, 32, 352, 70, 'nuclear', 0.7, 0.7, 33872, -96, 0, 0, 96, 96, 1585.12], + [46, 103, 40, 0, 40, -15, 1.01, 100, 1, 140, 0, 0.013717, -1.556667, 69, 135, 27, 'coal', 0.7, 0.7, 16123, -96, 0, 0, 4, 4, 1385.6], + [47, 104, 0, 0, 23, -8, 0.971, 100, 1, 100, 0, 0.043824, -4.543579, 138, 95, 19, 'gas', 0.7, 0.7, 7948, 96, 95, 1, 1, 1, 1902.08], + [48, 105, 0, 0, 23, -8, 0.965, 100, 1, 100, 0, 0.048828, -4.796, 139, 90, 18, 'gas', 0.7, 0.7, 9611, 96, 90, 1, 1, 1, 1819.97], + [49, 107, 0, 0, 200, -200, 0.952, 100, 1, 100, 0, 0.046728, -4.691739, 139, 92, 18, 'gas', 0.7, 0.7, 7920, 96, 92, 1, 1, 1, 1860.41], + [50, 110, 0, 0, 23, -8, 0.973, 100, 1, 100, 0, 0.029537, -2.284239, 70, 92, 18, 'coal', 0.7, 0.7, 11775, 96, 92, 1, 4, 4, 962.66], + [51, 111, 36, 0, 1000, -100, 0.98, 100, 1, 136, 0, 0.014348, -1.592045, 69, 132, 26, 'coal', 0.7, 0.7, 19880, 96, 132, 1, 4, 4, 1354.8], + [52, 112, 0, 0, 1000, -100, 0.975, 100, 1, 100, 0, 0.028293, -2.235638, 70, 94, 19, 'coal', 0.7, 0.7, 10897, -96, 0, 0, 4, 4, 983.58], + [53, 113, 0, 0, 200, -100, 0.993, 100, 1, 100, 0, 0.027701, -2.212105, 70, 95, 19, 'coal', 0.7, 0.7, 11855, 96, 95, 1, 4, 4, 994.05], + [54, 116, 0, 0, 1000, -1000, 1.005, 100, 1, 100, 0, 0.045729, -4.64129, 139, 93, 19, 'gas', 0.7, 0.7, 7749, -96, 0, 0, 1, 1, 1880.64] + ]) + + self.lines = DataFrame( + ['id', 'from', 'to', 'r', 'x', 'b', 'rateA', 'ratio', 'angle', 'status', 'floor', 'cap'], + [ + [1, 1, 2, 0.0303, 0.0999, 0.0254, 0, 0, 0, 1, 0, 0], + [2, 1, 3, 0.0129, 0.0424, 0.01082, 0, 0, 0, 1, 0, 0], + [3, 4, 5, 0.00176, 0.00798, 0.0021, 0, 0, 0, 1, 0, 0], + [4, 3, 5, 0.0241, 0.108, 0.0284, 0, 0, 0, 1, 0, 0], + [5, 5, 6, 0.0119, 0.054, 0.01426, 0, 0, 0, 1, 0, 0], + [6, 6, 7, 0.00459, 0.0208, 0.0055, 0, 0, 0, 1, 0, 0], + [7, 8, 9, 0.00244, 0.0305, 1.162, 0, 0, 0, 1, 0, 0], + [8, 8, 5, 0, 0.0267, 0, 0, 0.985, 0, 1, 0, 0], + [9, 9, 10, 0.00258, 0.0322, 1.23, 0, 0, 0, 1, 0, 0], + [10, 4, 11, 0.0209, 0.0688, 0.01748, 0, 0, 0, 1, 0, 0], + [11, 5, 11, 0.0203, 0.0682, 0.01738, 0, 0, 0, 1, 0, 0], + [12, 11, 12, 0.00595, 0.0196, 0.00502, 0, 0, 0, 1, 0, 0], + [13, 2, 12, 0.0187, 0.0616, 0.01572, 0, 0, 0, 1, 0, 0], + [14, 3, 12, 0.0484, 0.16, 0.0406, 0, 0, 0, 1, 0, 0], + [15, 7, 12, 0.00862, 0.034, 0.00874, 0, 0, 0, 1, 0, 0], + [16, 11, 13, 0.02225, 0.0731, 0.01876, 0, 0, 0, 1, 0, 0], + [17, 12, 14, 0.0215, 0.0707, 0.01816, 0, 0, 0, 1, 0, 0], + [18, 13, 15, 0.0744, 0.2444, 0.06268, 0, 0, 0, 1, 0, 0], + [19, 14, 15, 0.0595, 0.195, 0.0502, 0, 0, 0, 1, 0, 0], + [20, 12, 16, 0.0212, 0.0834, 0.0214, 0, 0, 0, 1, 0, 0], + [21, 15, 17, 0.0132, 0.0437, 0.0444, 0, 0, 0, 1, 0, 0], + [22, 16, 17, 0.0454, 0.1801, 0.0466, 0, 0, 0, 1, 0, 0], + [23, 17, 18, 0.0123, 0.0505, 0.01298, 0, 0, 0, 1, 0, 0], + [24, 18, 19, 0.01119, 0.0493, 0.01142, 0, 0, 0, 1, 0, 0], + [25, 19, 20, 0.0252, 0.117, 0.0298, 0, 0, 0, 1, 0, 0], + [26, 15, 19, 0.012, 0.0394, 0.0101, 0, 0, 0, 1, 0, 0], + [27, 20, 21, 0.0183, 0.0849, 0.0216, 0, 0, 0, 1, 0, 0], + [28, 21, 22, 0.0209, 0.097, 0.0246, 0, 0, 0, 1, 0, 0], + [29, 22, 23, 0.0342, 0.159, 0.0404, 0, 0, 0, 1, 0, 0], + [30, 23, 24, 0.0135, 0.0492, 0.0498, 0, 0, 0, 1, 0, 0], + [31, 23, 25, 0.0156, 0.08, 0.0864, 0, 0, 0, 1, 0, 0], + [32, 26, 25, 0, 0.0382, 0, 0, 0.96, 0, 1, 0, 0], + [33, 25, 27, 0.0318, 0.163, 0.1764, 0, 0, 0, 1, 0, 0], + [34, 27, 28, 0.01913, 0.0855, 0.0216, 0, 0, 0, 1, 0, 0], + [35, 28, 29, 0.0237, 0.0943, 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0, 0], + [173, 108, 109, 0.0105, 0.0288, 0.0076, 0, 0, 0, 1, 0, 0], + [174, 103, 110, 0.03906, 0.1813, 0.0461, 0, 0, 0, 1, 0, 0], + [175, 109, 110, 0.0278, 0.0762, 0.0202, 0, 0, 0, 1, 0, 0], + [176, 110, 111, 0.022, 0.0755, 0.02, 0, 0, 0, 1, 0, 0], + [177, 110, 112, 0.0247, 0.064, 0.062, 0, 0, 0, 1, 0, 0], + [178, 17, 113, 0.00913, 0.0301, 0.00768, 0, 0, 0, 1, 0, 0], + [179, 32, 113, 0.0615, 0.203, 0.0518, 0, 0, 0, 1, 0, 0], + [180, 32, 114, 0.0135, 0.0612, 0.01628, 0, 0, 0, 1, 0, 0], + [181, 27, 115, 0.0164, 0.0741, 0.01972, 0, 0, 0, 1, 0, 0], + [182, 114, 115, 0.0023, 0.0104, 0.00276, 0, 0, 0, 1, 0, 0], + [183, 68, 116, 0.00034, 0.00405, 0.164, 0, 1, 0, 1, 0, 0], + [184, 12, 117, 0.0329, 0.14, 0.0358, 0, 0, 0, 1, 0, 0], + [185, 75, 118, 0.0145, 0.0481, 0.01198, 0, 0, 0, 1, 0, 0], + [186, 76, 118, 0.0164, 0.0544, 0.01356, 0, 0, 0, 1, 0, 0] + ]) + + self.loads = DataFrame( + ['id', 'bus_id', 'Pd', 'Qd', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [ + [1, 1, 51, 27, 0, 0, 0, 51, 0], + 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31, 43, 27, 0, 0, 0, 43, 0], + [32, 32, 59, 23, 0, 0, 0, 59, 0], + [33, 33, 23, 9, 0, 0, 0, 23, 0], + [34, 34, 59, 26, 0, 0, 0, 59, 0], + [35, 35, 33, 9, 0, 0, 0, 33, 0], + [36, 36, 31, 17, 0, 0, 0, 31, 0], + [37, 37, 0, 0, 0, 0, 0, 0, 0], + [38, 38, 0, 0, 0, 0, 0, 0, 0], + [39, 39, 27, 11, 0, 0, 0, 27, 0], + [40, 40, 66, 23, 0, 0, 0, 66, 0], + [41, 41, 37, 10, 0, 0, 0, 37, 0], + [42, 42, 96, 23, 0, 0, 0, 96, 0], + [43, 43, 18, 7, 0, 0, 0, 18, 0], + [44, 44, 16, 8, 0, 0, 0, 16, 0], + [45, 45, 53, 22, 0, 0, 0, 53, 0], + [46, 46, 28, 10, 0, 0, 0, 28, 0], + [47, 47, 34, 0, 0, 0, 0, 34, 0], + [48, 48, 20, 11, 0, 0, 0, 20, 0], + [49, 49, 87, 30, 0, 0, 0, 87, 0], + [50, 50, 17, 4, 0, 0, 0, 17, 0], + [51, 51, 17, 8, 0, 0, 0, 17, 0], + [52, 52, 18, 5, 0, 0, 0, 18, 0], + [53, 53, 23, 11, 0, 0, 0, 23, 0], + [54, 54, 113, 32, 0, 0, 0, 113, 0], + [55, 55, 63, 22, 0, 0, 0, 63, 0], + [56, 56, 84, 18, 0, 0, 0, 84, 0], + [57, 57, 12, 3, 0, 0, 0, 12, 0], + [58, 58, 12, 3, 0, 0, 0, 12, 0], + [59, 59, 277, 113, 0, 0, 0, 277, 0], + [60, 60, 78, 3, 0, 0, 0, 78, 0], + [61, 61, 0, 0, 0, 0, 0, 0, 0], + [62, 62, 77, 14, 0, 0, 0, 77, 0], + [63, 63, 0, 0, 0, 0, 0, 0, 0], + [64, 64, 0, 0, 0, 0, 0, 0, 0], + [65, 65, 0, 0, 0, 0, 0, 0, 0], + [66, 66, 39, 18, 0, 0, 0, 39, 0], + [67, 67, 28, 7, 0, 0, 0, 28, 0], + [68, 68, 0, 0, 0, 0, 0, 0, 0], + [69, 69, 0, 0, 0, 0, 0, 0, 0], + [70, 70, 66, 20, 0, 0, 0, 66, 0], + [71, 71, 0, 0, 0, 0, 0, 0, 0], + [72, 72, 12, 0, 0, 0, 0, 12, 0], + [73, 73, 6, 0, 0, 0, 0, 6, 0], + [74, 74, 68, 27, 0, 0, 0, 68, 0], + [75, 75, 47, 11, 0, 0, 0, 47, 0], + [76, 76, 68, 36, 0, 0, 0, 68, 0], + [77, 77, 61, 28, 0, 0, 0, 61, 0], + [78, 78, 71, 26, 0, 0, 0, 71, 0], + [79, 79, 39, 32, 0, 0, 0, 39, 0], + [80, 80, 130, 26, 0, 0, 0, 130, 0], + [81, 81, 0, 0, 0, 0, 0, 0, 0], + [82, 82, 54, 27, 0, 0, 0, 54, 0], + [83, 83, 20, 10, 0, 0, 0, 20, 0], + [84, 84, 11, 7, 0, 0, 0, 11, 0], + [85, 85, 24, 15, 0, 0, 0, 24, 0], + [86, 86, 21, 10, 0, 0, 0, 21, 0], + [87, 87, 0, 0, 0, 0, 0, 0, 0], + [88, 88, 48, 10, 0, 0, 0, 48, 0], + [89, 89, 0, 0, 0, 0, 0, 0, 0], + [90, 90, 163, 42, 0, 0, 0, 163, 0], + [91, 91, 10, 0, 0, 0, 0, 10, 0], + [92, 92, 65, 10, 0, 0, 0, 65, 0], + [93, 93, 12, 7, 0, 0, 0, 12, 0], + [94, 94, 30, 16, 0, 0, 0, 30, 0], + [95, 95, 42, 31, 0, 0, 0, 42, 0], + [96, 96, 38, 15, 0, 0, 0, 38, 0], + [97, 97, 15, 9, 0, 0, 0, 15, 0], + [98, 98, 34, 8, 0, 0, 0, 34, 0], + [99, 99, 42, 0, 0, 0, 0, 42, 0], + [100, 100, 37, 18, 0, 0, 0, 37, 0], + [101, 101, 22, 15, 0, 0, 0, 22, 0], + [102, 102, 5, 3, 0, 0, 0, 5, 0], + [103, 103, 23, 16, 0, 0, 0, 23, 0], + [104, 104, 38, 25, 0, 0, 0, 38, 0], + [105, 105, 31, 26, 0, 0, 0, 31, 0], + [106, 106, 43, 16, 0, 0, 0, 43, 0], + [107, 107, 50, 12, 0, 0, 0, 50, 0], + [108, 108, 2, 1, 0, 0, 0, 2, 0], + [109, 109, 8, 3, 0, 0, 0, 8, 0], + [110, 110, 39, 30, 0, 0, 0, 39, 0], + [111, 111, 0, 0, 0, 0, 0, 0, 0], + [112, 112, 68, 13, 0, 0, 0, 68, 0], + [113, 113, 6, 0, 0, 0, 0, 6, 0], + [114, 114, 8, 3, 0, 0, 0, 8, 0], + [115, 115, 22, 7, 0, 0, 0, 22, 0], + [116, 116, 184, 0, 0, 0, 0, 184, 0], + [117, 117, 20, 8, 0, 0, 0, 20, 0], + [118, 118, 33, 15, 0, 0, 0, 33, 0] + ]) + + self.real_params = True + super().__init__(*args, **kwargs) + + +if __name__ == '__main__': + c = Case118() + c.check() + print(c.get_node_ptdf()) diff --git a/powergrid_case/transmission/Case1354pegase.py b/powergrid_case/transmission/Case1354pegase.py new file mode 100644 index 0000000000000000000000000000000000000000..ea7f124e6562b3d677d9a29fff45be5d95df4be3 --- /dev/null +++ b/powergrid_case/transmission/Case1354pegase.py @@ -0,0 +1,5039 @@ +"""Power System Case: 1354pegase + +Data Source: MATPOWER case file +Base MVA: 100.0 MVA +Base kV: 220.0 kV + +All values are in standard MATPOWER units (MW, MVAr, p.u.) + + +Nodes (bus) columns: + id, type, Pd, Qd, Gs, Bs, Vm, Va, baseKV, Vmax, Vmin + - type: 1=PQ, 2=PV, 3=Slack + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - Gs/Bs: Shunt conductance/susceptance (MW/MVAr at V=1.0 p.u.) + - Vm: Voltage magnitude (p.u.) + - Va: Voltage angle (degrees) + - baseKV: Base voltage (kV) + - Vmax/Vmin: Voltage limits (p.u.) + +Units (generators) columns: + id, bus_id, Pg, Qg, Qmax, Qmin, Vg, mBase, status, Pmax, Pmin, mc_a, mc_b, mc_c + - Pg/Qg: Active/Reactive power output (MW/MVAr) + - Qmax/Qmin: Reactive power limits (MVAr) + - Vg: Voltage setpoint (p.u.) + - mBase: Machine base (MVA) + - status: >0 in-service, <=0 out-of-service + - Pmax/Pmin: Active power limits (MW) + - mc_a/mc_b/mc_c: Marginal cost coefficients (quadratic) + +Lines (branches) columns: + id, from, to, r, x, b, rateA, ratio, angle, status, floor, cap + - r/x: Resistance/Reactance (p.u.) + - b: Line charging susceptance (p.u.) + - rateA: Long-term rating (MVA) + - ratio: Transformer tap ratio (0 for line) + - angle: Transformer phase shift (degrees) + - status: 1=in-service, 0=out-of-service + - floor/cap: Power flow limits (MW) + +Loads columns: + id, bus_id, Pd, Qd, mc_a, mc_b, mc_c, d_max, d_min + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - mc_a/mc_b/mc_c: Marginal utility coefficients + - d_max/d_min: Demand limits (MW) +""" +from math import inf + +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case1354pegase(ClearCase): + GRID_TYPE = "transmission" + BUS_COUNT = 1354 + VOLTAGE_LEVEL = "HV" + SOURCE = "MATPOWER" + DESCRIPTION = "European PEGASE 1354-bus system" + + def __init__(self, *args, **kwargs): + # System base values + self.baseMVA = 100.0 + self.baseKV = 220.0 + + # Node (bus) data + self.nodes = DataFrame( + ['id', 'type', 'Pd', 'Qd', 'Gs', 'Bs', 'Vm', 'Va', 'baseKV', 'Vmax', 'Vmin'], + [[3.0, 1.0, 151.0, 48.8, 0.0, 4.69, 1.016674, -21.761632, 220.0, 1.1, 0.9], + [4.0, 1.0, 171.41, 23.4, 0.0, 2.1, 1.026472, -7.007354, 220.0, 1.1, 0.9], + [10.0, 1.0, 134.0, 24.7, 0.0, 12.44, 1.038534, -24.281644, 220.0, 1.1, 0.9], + [21.0, 1.0, 161.2, 39.3, 0.0, 30.71, 1.036195, -21.958828, 220.0, 1.1, 0.9], + [22.0, 1.0, 0.0, -0.0, 0.0, 0.85, 1.035058, -18.483339, 220.0, 1.1, 0.9], + [26.0, 1.0, 167.3, 54.8, 0.0, 110.54, 1.032267, -3.318448, 380.0, 1.1, 0.9], + [29.0, 1.0, 152.9, 49.4, 0.0, 27.65, 0.994409, -13.816418, 380.0, 1.1, 0.9], + [44.0, 1.0, -0.0, 0.0, 0.0, 7.27, 1.045829, -22.181066, 220.0, 1.1, 0.9], + [53.0, 1.0, 48.65, 16.1, 0.0, 7.14, 1.063422, -9.070013, 220.0, 1.1, 0.9], + [58.0, 1.0, 0.0, 0.0, 0.0, 2.31, 0.983702, -21.159412, 380.0, 1.1, 0.9], + [59.0, 1.0, 119.2, 20.7, 0.0, 3.31, 1.036808, -23.631999, 220.0, 1.1, 0.9], + [90.0, 1.0, 363.25, 115.39, 0.0, 3.95, 1.042187, -27.546292, 220.0, 1.1, 0.9], + [96.0, 1.0, -8.4, 28.66, 0.0, 3.49, 1.030441, -15.689479, 220.0, 1.1, 0.9], + [113.0, 1.0, -0.0, -0.0, 0.0, 6.532711, 1.030718, -14.242909, 380.0, 1.1, 0.9], + [115.0, 1.0, 0.0, -0.0, 0.0, 4.21, 1.066797, -19.783678, 220.0, 1.1, 0.9], + [118.0, 1.0, 704.53, -35.33, 0.0, 13.102834, 1.020256, -11.430028, 380.0, 1.1, 0.9], + [124.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.081537, 8.330657, 220.0, 1.1, 0.9], + [128.0, 1.0, 23.73, 12.7, 0.0, 0.52, 1.020482, -16.063366, 220.0, 1.1, 0.9], + [145.0, 1.0, 38.34, 5.6, 0.0, 7.64, 1.039096, -8.903623, 220.0, 1.1, 0.9], + [148.0, 1.0, 32.34, 12.0, 0.0, 6.1, 1.041568, -7.991267, 220.0, 1.1, 0.9], + [150.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.062805, 2.531831, 220.0, 1.1, 0.9], + [163.0, 1.0, 147.76, 32.73, 0.0, 8.34, 1.047047, -10.672351, 220.0, 1.1, 0.9], + [171.0, 1.0, 100.8, 13.2, 0.0, 5.24, 1.069649, -25.153324, 220.0, 1.1, 0.9], + [174.0, 1.0, 370.5, -17.0, 0.0, 9.91, 1.074846, -27.942789, 220.0, 1.1, 0.9], + [184.0, 1.0, -0.0, -0.0, 0.0, 2.42, 1.042771, -11.94851, 220.0, 1.1, 0.9], + [188.0, 1.0, 36.84, 13.9, 0.0, 3.3, 1.018752, -19.550413, 220.0, 1.1, 0.9], + [195.0, 1.0, 73.14, 21.55, 0.0, 8.52, 1.056337, -8.791116, 220.0, 1.1, 0.9], + [196.0, 1.0, 0.0, -0.0, 0.0, 12.48, 1.074825, -26.319857, 220.0, 1.1, 0.9], + [198.0, 1.0, 39.74, 11.8, 0.0, 1.44, 1.01673, -16.306681, 220.0, 1.1, 0.9], + [207.0, 1.0, 321.98, 84.4, 0.0, 1.34, 1.026604, -13.457588, 220.0, 1.1, 0.9], + [216.0, 1.0, 155.6, 54.7, 0.0, 2.21, 1.039362, -24.590496, 220.0, 1.1, 0.9], + [217.0, 1.0, 105.2, 0.1, 0.0, 7.36, 1.042762, -2.603638, 220.0, 1.1, 0.9], + [218.0, 1.0, 69.83, 15.12, 0.0, 2.23, 1.045923, -13.114892, 220.0, 1.1, 0.9], + [221.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.984682, -21.807603, 380.0, 1.1, 0.9], + [225.0, 1.0, 0.0, 0.0, 0.0, 1.15, 1.063761, -20.174043, 220.0, 1.1, 0.9], + [280.0, 1.0, 119.6, 29.6, 0.0, 5.34, 1.035725, -11.193679, 220.0, 1.1, 0.9], + [283.0, 1.0, 27.33, 11.9, 0.0, 1.17, 1.035204, -12.094637, 220.0, 1.1, 0.9], + [292.0, 1.0, 13.82, 1.4, 0.0, 0.7, 1.047544, -14.765137, 220.0, 1.1, 0.9], + [305.0, 1.0, 103.0, 12.0, 0.0, 0.63, 1.067188, -32.434719, 220.0, 1.1, 0.9], + [306.0, 1.0, -0.0, 0.0, 0.0, 4.76, 1.030032, -18.823594, 220.0, 1.1, 0.9], + [314.0, 1.0, 163.1, 46.3, 0.0, 10.6, 1.005548, -16.020947, 220.0, 1.1, 0.9], + [333.0, 1.0, 524.5, 43.0, 0.0, 6.85, 1.014579, -42.137692, 220.0, 1.1, 0.9], + [338.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.048249, -6.162533, 220.0, 1.1, 0.9], + [346.0, 1.0, 197.5, 48.3, 0.0, 0.71, 1.040694, -21.298393, 220.0, 1.1, 0.9], + [350.0, 1.0, 110.4, 26.2, 0.0, 5.62, 1.043185, -24.295117, 220.0, 1.1, 0.9], + [352.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.055378, 0.262953, 380.0, 1.1, 0.9], + [367.0, 1.0, 65.17, -51.5, 0.0, 4.85, 1.07164, -23.599251, 220.0, 1.1, 0.9], + [401.0, 1.0, 56.5, 36.29, 0.0, 3.08, 1.026548, -14.262083, 220.0, 1.1, 0.9], + [408.0, 1.0, 129.1, 7.4, 0.0, 0.04, 1.039791, -11.549917, 220.0, 1.1, 0.9], + [410.0, 1.0, 170.89, 50.38, 0.0, 6.44, 1.041564, -26.439994, 220.0, 1.1, 0.9], + [413.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.05013, -6.606455, 220.0, 1.1, 0.9], + [416.0, 1.0, 70.68, 13.5, 0.0, 6.96, 1.0458, -6.728632, 220.0, 1.1, 0.9], + [426.0, 1.0, 123.1, 6.5, 0.0, 3.25, 1.040489, -18.395441, 220.0, 1.1, 0.9], + [432.0, 1.0, -0.0, -0.0, 0.0, 68.517663, 1.047774, 2.403578, 380.0, 1.1, 0.9], + [444.0, 1.0, 0.0, -0.0, 0.0, 2.45, 1.036267, -12.201434, 220.0, 1.1, 0.9], + [449.0, 1.0, 0.0, 0.0, 0.0, 29.42, 1.021739, -8.489958, 380.0, 1.1, 0.9], + [453.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.018914, -7.857046, 380.0, 1.1, 0.9], + [455.0, 1.0, 274.32, 5.66, 0.0, 13.24, 1.045882, -30.596498, 220.0, 1.1, 0.9], + [490.0, 1.0, 20.52, 4.0, 0.0, 2.77, 1.036451, -23.014287, 220.0, 1.1, 0.9], + [500.0, 1.0, 144.4, 35.5, 0.0, 7.66, 1.040423, -15.042452, 220.0, 1.1, 0.9], + [502.0, 1.0, -0.0, 0.0, 0.0, 1.96, 1.043564, -6.675538, 220.0, 1.1, 0.9], + [506.0, 1.0, -0.0, 0.0, 0.0, 0.4, 1.063297, -9.078728, 380.0, 1.1, 0.9], + [513.0, 1.0, 57.46, 17.1, 0.0, 1.61, 1.038461, -7.443414, 220.0, 1.1, 0.9], + [516.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.075592, -33.453515, 220.0, 1.1, 0.9], + [520.0, 1.0, 118.5, 20.4, 0.0, 2.57, 1.048239, -27.108761, 220.0, 1.1, 0.9], + [549.0, 1.0, 0.0, -0.0, 0.0, 5.15, 1.074517, -10.959606, 220.0, 1.1, 0.9], + [554.0, 1.0, 0.0, -0.0, 0.0, 1.97, 1.024071, -20.793083, 220.0, 1.1, 0.9], + [556.0, 1.0, 16.52, 9.0, 0.0, 1.17, 1.03694, -22.762979, 220.0, 1.1, 0.9], + [561.0, 1.0, 0.0, -0.0, 0.0, 0.32, 1.055451, -11.021763, 220.0, 1.1, 0.9], 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220.0, 1.1, 0.9], + [8961.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.035459, -14.187287, 220.0, 1.1, 0.9], + [8975.0, 1.0, 0.0, -0.0, 0.0, 11.04, 1.04225, -24.276259, 220.0, 1.1, 0.9], + [8976.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.046972, -17.074322, 220.0, 1.1, 0.9], + [8980.0, 1.0, 63.97, 12.8, 0.0, 0.17, 1.042994, -11.072487, 220.0, 1.1, 0.9], + [8989.0, 1.0, 88.5, 24.5, 0.0, 2.23, 1.043398, -25.575347, 220.0, 1.1, 0.9], + [8992.0, 1.0, -0.0, -0.0, 0.0, 14.64, 1.051114, -3.785395, 220.0, 1.1, 0.9], + [8997.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.997131, -13.27089, 380.0, 1.1, 0.9], + [8999.0, 1.0, 41.15, 10.3, 0.0, 2.41, 1.044391, -21.558302, 220.0, 1.1, 0.9], + [9002.0, 1.0, 119.02, 12.54, 0.0, 23.45, 1.021009, -10.528192, 220.0, 1.1, 0.9], + [9011.0, 1.0, 88.4, 25.2, 0.0, 12.9, 1.036275, -23.026084, 220.0, 1.1, 0.9], + [9012.0, 1.0, 25.63, 6.5, 0.0, 0.52, 1.048758, 1.093286, 220.0, 1.1, 0.9], + [9014.0, 1.0, 70.78, 19.6, 0.0, 8.1, 1.051072, -6.681904, 220.0, 1.1, 0.9], + [9018.0, 1.0, 55.46, 16.9, 0.0, 1.92, 1.022715, -6.602667, 220.0, 1.1, 0.9], + [9019.0, 1.0, 91.4, 18.1, 0.0, 4.89, 1.040421, -24.677298, 220.0, 1.1, 0.9], + [9021.0, 1.0, 152.18, 21.63, 0.0, 1.91, 1.035437, -6.308005, 220.0, 1.1, 0.9], + [9033.0, 1.0, 76.88, 16.4, 0.0, 6.61, 1.049786, -26.382004, 220.0, 1.1, 0.9], + [9045.0, 1.0, 60.57, 18.9, 0.0, 1.46, 1.039905, -24.629587, 220.0, 1.1, 0.9], + [9051.0, 1.0, 0.0, -0.0, 0.0, 2.15, 1.036594, 0.577238, 220.0, 1.1, 0.9], + [9059.0, 1.0, 0.0, -0.0, 0.0, 2.0, 1.072487, -27.192131, 220.0, 1.1, 0.9], + [9065.0, 1.0, -0.0, -0.0, 0.0, 0.59, 1.040021, 2.414524, 380.0, 1.1, 0.9], + [9066.0, 1.0, 23.26, 3.01, 0.0, 9.29, 1.019989, -20.806005, 220.0, 1.1, 0.9], + [9067.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.040924, 1.549232, 220.0, 1.1, 0.9], + [9091.0, 1.0, 0.0, 0.0, 0.0, 3.65, 1.038554, -9.767436, 220.0, 1.1, 0.9], + [9101.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.02885, -21.628013, 380.0, 1.1, 0.9], + [9108.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.046626, -16.441009, 220.0, 1.1, 0.9], + [9109.0, 1.0, 0.0, -0.0, 0.0, 0.31, 1.036596, 0.577218, 220.0, 1.1, 0.9], + [9112.0, 1.0, 0.0, -0.0, 0.0, 19.71, 1.047611, -12.93238, 220.0, 1.1, 0.9], + [9119.0, 1.0, -0.0, 0.0, 0.0, 1.24, 1.04289, -20.527494, 220.0, 1.1, 0.9], + [9128.0, 1.0, 50.56, 8.7, 0.0, 0.19, 1.042244, -2.676445, 220.0, 1.1, 0.9], + [9130.0, 1.0, 245.51, 9.17, 0.0, 24.25, 1.049965, -30.721639, 220.0, 1.1, 0.9], + [9131.0, 1.0, -0.0, -0.0, 0.0, 6.62, 1.051124, -24.097314, 220.0, 1.1, 0.9], + [9137.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.049768, -26.378636, 220.0, 1.1, 0.9], + [9140.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.049624, -5.232971, 220.0, 1.1, 0.9], + [9150.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.037969, -13.200551, 380.0, 1.1, 0.9], + [9155.0, 1.0, -0.0, -0.0, 0.0, 5.01, 1.02382, -20.860292, 220.0, 1.1, 0.9], + [9158.0, 1.0, 54.96, 9.42, 0.0, 5.92, 1.025798, -14.56483, 220.0, 1.1, 0.9], + [9164.0, 1.0, 7.71, 2.4, 0.0, 6.93, 1.001887, -19.403088, 220.0, 1.1, 0.9], + [9173.0, 1.0, 66.07, 15.6, 0.0, 5.57, 1.032906, -20.202148, 220.0, 1.1, 0.9], + [9174.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.03623, -32.377948, 380.0, 1.1, 0.9], + [9176.0, 1.0, -0.0, 0.0, 0.0, 1.28, 1.047842, -12.93497, 220.0, 1.1, 0.9], + [9180.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.061189, -8.603491, 220.0, 1.1, 0.9], + [9181.0, 1.0, 2.43, 1.35, 0.0, 0.1, 1.032498, -9.466095, 220.0, 1.1, 0.9], + [9185.0, 1.0, 66.97, 18.6, 0.0, 18.5, 1.051815, -6.62338, 220.0, 1.1, 0.9], + [9189.0, 1.0, 62.57, -61.0, 0.0, 55.14, 1.048019, -25.022568, 220.0, 1.1, 0.9], + [9191.0, 1.0, -0.0, -0.0, 0.0, 2.34, 1.073685, -24.80852, 220.0, 1.1, 0.9], + [9203.0, 1.0, 627.36, -73.13, 0.0, 27.185221, 1.001613, -12.605605, 380.0, 1.1, 0.9], + [9213.0, 1.0, -0.0, -0.0, 0.0, 10.210952, 1.023742, -4.653017, 380.0, 1.1, 0.9], + [9217.0, 1.0, -0.0, 0.0, 0.0, 6.33, 1.040155, -8.875709, 220.0, 1.1, 0.9], + [9222.0, 1.0, -5.15, -2.04, 0.0, 154.446402, 1.053345, -16.073005, 380.0, 1.1, 0.9], + [9231.0, 1.0, 242.08, 59.98, 0.0, 5.6, 1.029833, -19.150137, 220.0, 1.1, 0.9], + [9241.0, 1.0, 0.0, -0.0, 0.0, 0.36, 1.049081, -9.481609, 220.0, 1.1, 0.9]]) + + # Generator (unit) data + self.units = DataFrame( + ['id', 'bus_id', 'Pg', 'Qg', 'Qmax', 'Qmin', 'Vg', 'mBase', 'status', 'Pmax', 'Pmin', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min'], + [[1.0, 124.0, 861.3, 56.53, 440.32, -172.59, 1.081537, 100.0, 1.0, 1000.0, 333.33, 0.0, 0.0, 1.0, 1000.0, 333.33], + [2.0, 150.0, 67.29, -7.99, 77.09, -22.54, 1.062805, 100.0, 1.0, 160.0, 0.0, 0.0, 0.0, 1.0, 160.0, 0.0], + [3.0, 221.0, -155.39, 97.68, 183.92, -65.3, 0.984682, 100.0, 1.0, 100.0, -207.18, 0.0, 0.0, 1.0, 100.0, -207.18], + [4.0, 338.0, 83.7, 2.5, 55.54, -19.16, 1.048249, 100.0, 1.0, 120.0, 0.0, 0.0, 0.0, 1.0, 120.0, 0.0], + [5.0, 352.0, 1250.4, 278.94, 926.35, -297.68, 1.055378, 100.0, 1.0, 2000.0, 666.67, 0.0, 0.0, 1.0, 2000.0, 666.67], + [6.0, 413.0, 231.0, 19.11, 124.12, -49.84, 1.05013, 100.0, 1.0, 280.0, 0.0, 0.0, 0.0, 1.0, 280.0, 0.0], + [7.0, 453.0, 260.1, 57.98, 257.23, -74.4, 1.018914, 100.0, 1.0, 540.0, 0.0, 0.0, 0.0, 1.0, 540.0, 0.0], + [8.0, 516.0, 539.4, 190.43, 261.79, -106.67, 1.075592, 100.0, 1.0, 600.0, 200.0, 0.0, 0.0, 1.0, 600.0, 200.0], + [9.0, 564.0, -51.67, -3.31, 18.47, -19.35, 1.069817, 100.0, 1.0, 100.0, -68.89, 0.0, 0.0, 1.0, 100.0, -68.89], + [10.0, 583.0, -270.0, 3.65, 17.88, -7.03, 1.045397, 100.0, 1.0, 100.0, -360.0, 0.0, 0.0, 1.0, 100.0, -360.0], + [11.0, 615.0, 38.2, -0.39, 17.09, -7.79, 1.063876, 100.0, 1.0, 40.0, 0.0, 0.0, 0.0, 1.0, 40.0, 0.0], + [12.0, 616.0, 379.2, 37.76, 217.9, -81.16, 1.048713, 100.0, 1.0, 480.0, 160.0, 0.0, 0.0, 1.0, 480.0, 160.0], + [13.0, 639.0, -46.2, 112.55, 135.52, -38.9, 1.051376, 100.0, 1.0, 100.0, -61.6, 0.0, 0.0, 1.0, 100.0, -61.6], + [14.0, 682.0, 37.4, 8.53, 38.77, -11.06, 1.0691, 100.0, 1.0, 80.0, 0.0, 0.0, 0.0, 1.0, 80.0, 0.0], + [15.0, 749.0, 198.88, -11.17, 105.69, -43.84, 1.057884, 100.0, 1.0, 240.0, 0.0, 0.0, 0.0, 1.0, 240.0, 0.0], + [16.0, 757.0, 116.7, 13.66, 51.3, -23.41, 1.017567, 100.0, 1.0, 120.0, 0.0, 0.0, 0.0, 1.0, 120.0, 0.0], + [17.0, 776.0, -111.4, 3.36, 18.16, 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100.0, 1.0, 100.0, -49.6, 0.0, 0.0, 1.0, 100.0, -49.6], + [258.0, 9150.0, 860.8, 117.32, 439.38, -173.28, 1.037969, 100.0, 1.0, 1000.0, 333.33, 0.0, 0.0, 1.0, 1000.0, 333.33], + [259.0, 9174.0, -331.4, 142.7, 175.0, -49.16, 1.03623, 100.0, 1.0, 100.0, -441.87, 0.0, 0.0, 1.0, 100.0, -441.87], + [260.0, 9180.0, 72.0, 7.71, 77.69, -21.97, 1.061189, 100.0, 1.0, 160.0, 0.0, 0.0, 0.0, 1.0, 160.0, 0.0]]) + + # Branch (line) data + self.lines = DataFrame( + ['id', 'from', 'to', 'r', 'x', 'b', 'rateA', 'ratio', 'angle', 'status', 'floor', 'cap'], + [[1.0, 7351.0, 5441.0, 0.00018, 0.000781, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [2.0, 4314.0, 7571.0, 0.002961, 0.01669, 0.0, 319.0, 0.0, 0.0, 1.0, -319.0, 319.0], + [3.0, 5803.0, 3916.0, 0.00056, 0.00432, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [4.0, 6757.0, 6036.0, 0.0002, 0.00246, 0.0, 657.0, 0.0, 0.0, 1.0, -657.0, 657.0], + [5.0, 6757.0, 6921.0, 0.0003, 0.00377, 0.0, 1315.0, 0.0, 0.0, 1.0, -1315.0, 1315.0], + [6.0, 5019.0, 9112.0, 0.00014, 0.00057, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [7.0, 2930.0, 9112.0, 0.00013, 0.000729, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [8.0, 1436.0, 9112.0, 0.00012, 0.000581, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [9.0, 1851.0, 9112.0, 0.00011, 0.00064, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [10.0, 8331.0, 9112.0, 0.00019, 0.00056, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [11.0, 6220.0, 8791.0, 0.00062, 0.004909, 0.0, 529.0, 0.0, 0.0, 1.0, -529.0, 529.0], + [12.0, 9203.0, 7842.0, 7e-05, 0.00076, 0.0, 887.0, 0.0, 0.0, 1.0, -887.0, 887.0], + [13.0, 9203.0, 8997.0, 0.00066, 0.00622, 0.0, 1611.0, 0.0, 0.0, 1.0, -1611.0, 1611.0], + [14.0, 9203.0, 2129.0, 0.00054, 0.00752, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [15.0, 9203.0, 29.0, 0.00105, 0.00877, 0.0, 1315.0, 0.0, 0.0, 1.0, -1315.0, 1315.0], + [16.0, 118.0, 8903.0, 8e-05, 0.00091, 0.0, 657.0, 0.0, 0.0, 1.0, -657.0, 657.0], + [17.0, 118.0, 4598.0, 0.00056, 0.00719, 0.0, 953.0, 0.0, 0.0, 1.0, -953.0, 953.0], + [18.0, 2426.0, 5533.0, 0.000531, 0.002039, 0.0, 319.0, 0.0, 0.0, 1.0, -319.0, 319.0], + [19.0, 2426.0, 4831.0, 0.008659, 0.03769, 0.0, 300.0, 0.0, 0.0, 1.0, -300.0, 300.0], + [20.0, 2426.0, 8961.0, 0.003849, 0.021099, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [21.0, 2426.0, 8522.0, 0.00688, 0.035969, 0.0, 300.0, 0.0, 0.0, 1.0, -300.0, 300.0], + [22.0, 2426.0, 6888.0, 0.006729, 0.03713, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [23.0, 2426.0, 3401.0, 0.00111, 0.006651, 0.0, 414.0, 0.0, 0.0, 1.0, -414.0, 414.0], + [24.0, 2426.0, 641.0, 0.0023, 0.008909, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [25.0, 2426.0, 2600.0, 0.000841, 0.00313, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [26.0, 2426.0, 5351.0, 0.003521, 0.017479, 0.0, 300.0, 0.0, 0.0, 1.0, -300.0, 300.0], + [27.0, 3051.0, 718.0, 3.9e-05, 0.00025, 0.0, 510.0, 0.0, 0.0, 1.0, -510.0, 510.0], + [28.0, 3036.0, 2327.0, 0.000159, 0.000729, 0.0, 357.0, 0.0, 0.0, 1.0, -357.0, 357.0], + [29.0, 8651.0, 7473.0, 0.005281, 0.032099, 0.0, 395.0, 0.0, 0.0, 1.0, -395.0, 395.0], + [30.0, 8651.0, 7473.0, 0.005651, 0.029419, 0.0, 376.0, 0.0, 0.0, 1.0, -376.0, 376.0], + [31.0, 903.0, 3654.0, 0.000271, 0.00036, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [32.0, 8732.0, 7050.0, 0.00044, 0.00143, 0.0, 472.0, 0.0, 0.0, 1.0, -472.0, 472.0], + [33.0, 8732.0, 3912.0, 0.000159, 0.00074, 0.0, 453.0, 0.0, 0.0, 1.0, -453.0, 453.0], + [34.0, 2273.0, 1973.0, 0.00019, 0.000591, 0.0, 338.0, 0.0, 0.0, 1.0, -338.0, 338.0], + [35.0, 5131.0, 2928.0, 0.00019, 0.00087, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [36.0, 6629.0, 4918.0, 0.002591, 0.013659, 0.0, 319.0, 0.0, 0.0, 1.0, -319.0, 319.0], + [37.0, 6629.0, 7309.0, 0.00305, 0.01168, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [38.0, 413.0, 1102.0, 0.000159, 0.000599, 0.0, 433.0, 0.0, 0.0, 1.0, -433.0, 433.0], + [39.0, 413.0, 1102.0, 0.000159, 0.00062, 0.0, 395.0, 0.0, 0.0, 1.0, -395.0, 395.0], + [40.0, 3248.0, 4918.0, 0.00101, 0.004229, 0.0, 472.0, 0.0, 0.0, 1.0, -472.0, 472.0], + [41.0, 3248.0, 4281.0, 0.00319, 0.018651, 0.0, 453.0, 0.0, 0.0, 1.0, -453.0, 453.0], + 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0.0], + [54.0, 3218.0, 7809.0, 0.005271, 0.01906, 0.0, 281.0, 0.0, 0.0, 1.0, -281.0, 281.0], + [55.0, 3218.0, 5455.0, 0.00906, 0.053151, 0.0, 319.0, 0.0, 0.0, 1.0, -319.0, 319.0], + [56.0, 3218.0, 1857.0, 0.00405, 0.0153, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [57.0, 6806.0, 5410.0, 0.00055, 0.003961, 0.0, 395.0, 0.0, 0.0, 1.0, -395.0, 395.0], + [58.0, 6806.0, 5410.0, 0.00055, 0.003729, 0.0, 338.0, 0.0, 0.0, 1.0, -338.0, 338.0], + [59.0, 6806.0, 1609.0, 0.00107, 0.007789, 0.0, 414.0, 0.0, 0.0, 1.0, -414.0, 414.0], + [60.0, 6806.0, 1609.0, 0.00112, 0.00775, 0.0, 472.0, 0.0, 0.0, 1.0, -472.0, 472.0], + [61.0, 6806.0, 1609.0, 0.001031, 0.00775, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [62.0, 6806.0, 2438.0, 0.00062, 0.003219, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [63.0, 6806.0, 954.0, 0.00068, 0.002659, 0.0, 414.0, 0.0, 0.0, 1.0, -414.0, 414.0], + [64.0, 9140.0, 502.0, 0.00193, 0.012479, 0.0, 491.0, 0.0, 0.0, 1.0, -491.0, 491.0], + [65.0, 9140.0, 3013.0, 0.001159, 0.007229, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [66.0, 9140.0, 2949.0, 0.00137, 0.008729, 0.0, 395.0, 0.0, 0.0, 1.0, -395.0, 395.0], + [67.0, 9140.0, 2949.0, 0.001401, 0.00855, 0.0, 433.0, 0.0, 0.0, 1.0, -433.0, 433.0], + [68.0, 9140.0, 2949.0, 0.001331, 0.008521, 0.0, 433.0, 0.0, 0.0, 1.0, -433.0, 433.0], + [69.0, 7070.0, 2208.0, 0.00031, 0.00081, 0.0, 281.0, 0.0, 0.0, 1.0, -281.0, 281.0], + [70.0, 7070.0, 8060.0, 0.000341, 0.00119, 0.0, 281.0, 0.0, 0.0, 1.0, -281.0, 281.0], + [71.0, 7070.0, 4484.0, 0.00031, 0.001281, 0.0, 376.0, 0.0, 0.0, 1.0, -376.0, 376.0], + [72.0, 7070.0, 4239.0, 0.00094, 0.0035, 0.0, 433.0, 0.0, 0.0, 1.0, -433.0, 433.0], + [73.0, 8535.0, 7047.0, 7e-05, 0.000651, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [74.0, 5477.0, 3657.0, 0.00019, 0.00124, 0.0, 491.0, 0.0, 0.0, 1.0, -491.0, 491.0], + [75.0, 5477.0, 2928.0, 0.000331, 0.002539, 0.0, 433.0, 0.0, 0.0, 1.0, -433.0, 433.0], + [76.0, 3145.0, 2918.0, 0.0016, 0.02113, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [77.0, 7770.0, 5317.0, 0.000909, 0.004711, 0.0, 357.0, 0.0, 0.0, 1.0, -357.0, 357.0], + [78.0, 7770.0, 5317.0, 0.00088, 0.004969, 0.0, 319.0, 0.0, 0.0, 1.0, -319.0, 319.0], + [79.0, 3.0, 8676.0, 0.001841, 0.0088, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [80.0, 3.0, 8189.0, 0.01013, 0.04238, 0.0, 395.0, 0.0, 0.0, 1.0, -395.0, 395.0], + [81.0, 7267.0, 2938.0, 0.00059, 0.00802, 0.0, 723.0, 0.0, 0.0, 1.0, -723.0, 723.0], + [82.0, 7267.0, 2938.0, 0.00054, 0.0079, 0.0, 657.0, 0.0, 0.0, 1.0, -657.0, 657.0], + [83.0, 7267.0, 3918.0, 0.00171, 0.02128, 0.0, 986.0, 0.0, 0.0, 1.0, -986.0, 986.0], + [84.0, 7267.0, 3918.0, 0.00174, 0.02084, 0.0, 854.0, 0.0, 0.0, 1.0, -854.0, 854.0], + [85.0, 7267.0, 6581.0, 0.00086, 0.01433, 0.0, 1151.0, 0.0, 0.0, 1.0, -1151.0, 1151.0], + [86.0, 7267.0, 6581.0, 0.00087, 0.01404, 0.0, 723.0, 0.0, 0.0, 1.0, -723.0, 723.0], + [87.0, 7267.0, 3830.0, 0.00126, 0.01447, 0.0, 1118.0, 0.0, 0.0, 1.0, -1118.0, 1118.0], + [88.0, 7267.0, 5648.0, 0.00122, 0.01509, 0.0, 1052.0, 0.0, 0.0, 1.0, -1052.0, 1052.0], + 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0.024893, 0.0, 591.0, 0.979227, 0.0, 1.0, -591.0, 591.0], + [1961.0, 3577.0, 5907.0, 0.000438, 0.02457, 0.0, 591.0, 0.979227, 0.0, 1.0, -591.0, 591.0], + [1962.0, 3577.0, 5907.0, 0.000365, 0.023986, 0.0, 591.0, 0.979227, 0.0, 1.0, -591.0, 591.0], + [1963.0, 7164.0, 5918.0, 0.000375, 0.023267, 0.0, 591.0, 0.979227, 0.0, 1.0, -591.0, 591.0], + [1964.0, 7164.0, 5918.0, 0.000323, 0.026375, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1965.0, 1798.0, 2467.0, 0.000334, 0.029735, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1966.0, 1798.0, 2467.0, 0.000313, 0.030237, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1967.0, 3346.0, 2132.0, 0.000767, 0.044049, 0.0, 0.0, 0.982143, 0.0, 1.0, 0.0, 0.0], + [1968.0, 3346.0, 2132.0, 0.000302, 0.026072, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1969.0, 3346.0, 2132.0, 0.00085, 0.039892, 0.0, 0.0, 0.982143, 0.0, 1.0, 0.0, 0.0], + [1970.0, 3483.0, 8992.0, 0.000344, 0.024956, 0.0, 591.0, 0.979227, 0.0, 1.0, -591.0, 591.0], + [1971.0, 8886.0, 8992.0, 0.000334, 0.026666, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1972.0, 2093.0, 805.0, 0.000365, 0.023788, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1973.0, 2093.0, 805.0, 0.000365, 0.023465, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1974.0, 221.0, 1541.0, 0.000334, 0.026447, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1975.0, 8347.0, 5383.0, 0.000323, 0.027042, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1976.0, 8347.0, 5383.0, 0.000313, 0.02748, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1977.0, 8347.0, 5383.0, 0.000302, 0.028314, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1978.0, 8347.0, 7507.0, 0.000323, 0.025853, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1979.0, 8347.0, 7507.0, 0.000365, 0.026197, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1980.0, 8347.0, 7507.0, 0.000365, 0.025165, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1981.0, 4000.0, 4852.0, 0.000355, 0.024237, 0.0, 591.0, 0.979227, 0.0, 1.0, -591.0, 591.0], + [1982.0, 4000.0, 2012.0, 0.000375, 0.024247, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1983.0, 2183.0, 4852.0, 0.000365, 0.023267, 0.0, 591.0, 0.979227, 0.0, 1.0, -591.0, 591.0], + [1984.0, 2183.0, 2012.0, 0.000342, 0.023139, 0.0, 591.0, 0.982143, 0.0, 1.0, -591.0, 591.0], + [1985.0, 1642.0, 7098.0, 0.000344, 0.026666, 0.0, 591.0, 0.979227, 0.0, 1.0, -591.0, 591.0], + [1986.0, 1642.0, 687.0, 0.000334, 0.027021, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1987.0, 809.0, 7098.0, 0.000302, 0.027615, 0.0, 591.0, 0.979227, 0.0, 1.0, -591.0, 591.0], + [1988.0, 809.0, 687.0, 0.000313, 0.026135, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1989.0, 4594.0, 8804.0, 0.000365, 0.025905, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1990.0, 4594.0, 8804.0, 0.000355, 0.025238, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0], + [1991.0, 2919.0, 4215.0, 0.000334, 0.026814, 0.0, 591.0, 0.93617, 0.0, 1.0, -591.0, 591.0]]) + + # Load data + self.loads = DataFrame( + ['id', 'bus_id', 'Pd', 'Qd', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1.0, 3.0, 151.0, 48.8, 0.0, 0.0, 0.0, 151.0, 151.0], + [2.0, 4.0, 171.41, 23.4, 0.0, 0.0, 0.0, 171.41, 171.41], + [3.0, 10.0, 134.0, 24.7, 0.0, 0.0, 0.0, 134.0, 134.0], + [4.0, 21.0, 161.2, 39.3, 0.0, 0.0, 0.0, 161.2, 161.2], + [5.0, 22.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [6.0, 26.0, 167.3, 54.8, 0.0, 0.0, 0.0, 167.3, 167.3], + [7.0, 29.0, 152.9, 49.4, 0.0, 0.0, 0.0, 152.9, 152.9], + [8.0, 44.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [9.0, 53.0, 48.65, 16.1, 0.0, 0.0, 0.0, 48.65, 48.65], + [10.0, 58.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [11.0, 59.0, 119.2, 20.7, 0.0, 0.0, 0.0, 119.2, 119.2], + [12.0, 90.0, 363.25, 115.39, 0.0, 0.0, 0.0, 363.25, 363.25], + [13.0, 96.0, -8.4, 28.66, 0.0, 0.0, 0.0, -8.4, -8.4], + [14.0, 113.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [15.0, 115.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [16.0, 118.0, 704.53, -35.33, 0.0, 0.0, 0.0, 704.53, 704.53], + [17.0, 124.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [18.0, 128.0, 23.73, 12.7, 0.0, 0.0, 0.0, 23.73, 23.73], + [19.0, 145.0, 38.34, 5.6, 0.0, 0.0, 0.0, 38.34, 38.34], + [20.0, 148.0, 32.34, 12.0, 0.0, 0.0, 0.0, 32.34, 32.34], + [21.0, 150.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [22.0, 163.0, 147.76, 32.73, 0.0, 0.0, 0.0, 147.76, 147.76], + [23.0, 171.0, 100.8, 13.2, 0.0, 0.0, 0.0, 100.8, 100.8], + [24.0, 174.0, 370.5, -17.0, 0.0, 0.0, 0.0, 370.5, 370.5], + [25.0, 184.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [26.0, 188.0, 36.84, 13.9, 0.0, 0.0, 0.0, 36.84, 36.84], + [27.0, 195.0, 73.14, 21.55, 0.0, 0.0, 0.0, 73.14, 73.14], + [28.0, 196.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [29.0, 198.0, 39.74, 11.8, 0.0, 0.0, 0.0, 39.74, 39.74], + [30.0, 207.0, 321.98, 84.4, 0.0, 0.0, 0.0, 321.98, 321.98], + [31.0, 216.0, 155.6, 54.7, 0.0, 0.0, 0.0, 155.6, 155.6], + [32.0, 217.0, 105.2, 0.1, 0.0, 0.0, 0.0, 105.2, 105.2], + [33.0, 218.0, 69.83, 15.12, 0.0, 0.0, 0.0, 69.83, 69.83], + [34.0, 221.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [35.0, 225.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [36.0, 280.0, 119.6, 29.6, 0.0, 0.0, 0.0, 119.6, 119.6], + [37.0, 283.0, 27.33, 11.9, 0.0, 0.0, 0.0, 27.33, 27.33], + [38.0, 292.0, 13.82, 1.4, 0.0, 0.0, 0.0, 13.82, 13.82], + [39.0, 305.0, 103.0, 12.0, 0.0, 0.0, 0.0, 103.0, 103.0], + [40.0, 306.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [41.0, 314.0, 163.1, 46.3, 0.0, 0.0, 0.0, 163.1, 163.1], + [42.0, 333.0, 524.5, 43.0, 0.0, 0.0, 0.0, 524.5, 524.5], + [43.0, 338.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [44.0, 346.0, 197.5, 48.3, 0.0, 0.0, 0.0, 197.5, 197.5], + [45.0, 350.0, 110.4, 26.2, 0.0, 0.0, 0.0, 110.4, 110.4], + [46.0, 352.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [47.0, 367.0, 65.17, -51.5, 0.0, 0.0, 0.0, 65.17, 65.17], + [48.0, 401.0, 56.5, 36.29, 0.0, 0.0, 0.0, 56.5, 56.5], + [49.0, 408.0, 129.1, 7.4, 0.0, 0.0, 0.0, 129.1, 129.1], + [50.0, 410.0, 170.89, 50.38, 0.0, 0.0, 0.0, 170.89, 170.89], + [51.0, 413.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [52.0, 416.0, 70.68, 13.5, 0.0, 0.0, 0.0, 70.68, 70.68], + [53.0, 426.0, 123.1, 6.5, 0.0, 0.0, 0.0, 123.1, 123.1], + [54.0, 432.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [55.0, 444.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [56.0, 449.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [57.0, 453.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [58.0, 455.0, 274.32, 5.66, 0.0, 0.0, 0.0, 274.32, 274.32], + [59.0, 490.0, 20.52, 4.0, 0.0, 0.0, 0.0, 20.52, 20.52], + [60.0, 500.0, 144.4, 35.5, 0.0, 0.0, 0.0, 144.4, 144.4], + [61.0, 502.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [62.0, 506.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [63.0, 513.0, 57.46, 17.1, 0.0, 0.0, 0.0, 57.46, 57.46], + [64.0, 516.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [65.0, 520.0, 118.5, 20.4, 0.0, 0.0, 0.0, 118.5, 118.5], + [66.0, 549.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [67.0, 554.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [68.0, 556.0, 16.52, 9.0, 0.0, 0.0, 0.0, 16.52, 16.52], + [69.0, 561.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [70.0, 564.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [71.0, 575.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [72.0, 583.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [73.0, 594.0, 67.57, 17.0, 0.0, 0.0, 0.0, 67.57, 67.57], + [74.0, 601.0, 140.6, 42.6, 0.0, 0.0, 0.0, 140.6, 140.6], + [75.0, 604.0, 33.24, 4.4, 0.0, 0.0, 0.0, 33.24, 33.24], + [76.0, 608.0, 150.9, 10.4, 0.0, 0.0, 0.0, 150.9, 150.9], + [77.0, 609.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [78.0, 615.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [79.0, 616.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [80.0, 619.0, 72.88, 14.4, 0.0, 0.0, 0.0, 72.88, 72.88], + [81.0, 639.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [82.0, 641.0, 45.32, 18.5, 0.0, 0.0, 0.0, 45.32, 45.32], + [83.0, 658.0, 258.4, 66.7, 0.0, 0.0, 0.0, 258.4, 258.4], + [84.0, 661.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [85.0, 666.0, -5.61, -2.79, 0.0, 0.0, 0.0, -5.61, -5.61], + [86.0, 678.0, 232.1, 89.8, 0.0, 0.0, 0.0, 232.1, 232.1], + [87.0, 682.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [88.0, 687.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [89.0, 707.0, 83.99, 21.2, 0.0, 0.0, 0.0, 83.99, 83.99], + [90.0, 718.0, 135.11, 41.0, 0.0, 0.0, 0.0, 135.11, 135.11], + [91.0, 720.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [92.0, 726.0, 400.3, 189.9, 0.0, 0.0, 0.0, 400.3, 400.3], + [93.0, 742.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [94.0, 747.0, 69.58, 16.0, 0.0, 0.0, 0.0, 69.58, 69.58], + [95.0, 749.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [96.0, 750.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [97.0, 757.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [98.0, 766.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [99.0, 769.0, 152.57, 40.0, 0.0, 0.0, 0.0, 152.57, 152.57], + [100.0, 772.0, 343.9, 141.9, 0.0, 0.0, 0.0, 343.9, 343.9], + [101.0, 776.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [102.0, 778.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [103.0, 789.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [104.0, 795.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [105.0, 800.0, 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8515.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1235.0, 8522.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1236.0, 8535.0, 72.68, 24.3, 0.0, 0.0, 0.0, 72.68, 72.68], + [1237.0, 8542.0, 87.7, 26.0, 0.0, 0.0, 0.0, 87.7, 87.7], + [1238.0, 8546.0, 5.01, 1.8, 0.0, 0.0, 0.0, 5.01, 5.01], + [1239.0, 8560.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1240.0, 8564.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1241.0, 8568.0, 175.7, 56.2, 0.0, 0.0, 0.0, 175.7, 175.7], + [1242.0, 8578.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1243.0, 8592.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1244.0, 8626.0, 136.0, 36.1, 0.0, 0.0, 0.0, 136.0, 136.0], + [1245.0, 8627.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1246.0, 8628.0, 277.1, 37.0, 0.0, 0.0, 0.0, 277.1, 277.1], + [1247.0, 8636.0, 31.43, 10.6, 0.0, 0.0, 0.0, 31.43, 31.43], + [1248.0, 8651.0, 162.49, 45.11, 0.0, 0.0, 0.0, 162.49, 162.49], + [1249.0, 8653.0, 44.55, 7.5, 0.0, 0.0, 0.0, 44.55, 44.55], + [1250.0, 8656.0, 5.51, 1.3, 0.0, 0.0, 0.0, 5.51, 5.51], + 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91.6, 0.0, 0.0, 0.0, 410.3, 410.3], + [1285.0, 8854.0, 69.18, 35.1, 0.0, 0.0, 0.0, 69.18, 69.18], + [1286.0, 8860.0, 57.16, 19.7, 0.0, 0.0, 0.0, 57.16, 57.16], + [1287.0, 8864.0, 63.31, -9.8, 0.0, 0.0, 0.0, 63.31, 63.31], + [1288.0, 8872.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1289.0, 8873.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1290.0, 8874.0, 285.2, 61.4, 0.0, 0.0, 0.0, 285.2, 285.2], + [1291.0, 8877.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1292.0, 8879.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1293.0, 8886.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1294.0, 8887.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1295.0, 8893.0, 278.3, 33.6, 0.0, 0.0, 0.0, 278.3, 278.3], + [1296.0, 8900.0, 3.1, 1.6, 0.0, 0.0, 0.0, 3.1, 3.1], + [1297.0, 8903.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1298.0, 8906.0, 91.0, 21.0, 0.0, 0.0, 0.0, 91.0, 91.0], + [1299.0, 8913.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1300.0, 8930.0, 139.4, 21.2, 0.0, 0.0, 0.0, 139.4, 139.4], + [1301.0, 8931.0, -0.56, 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152.18, 21.63, 0.0, 0.0, 0.0, 152.18, 152.18], + [1319.0, 9033.0, 76.88, 16.4, 0.0, 0.0, 0.0, 76.88, 76.88], + [1320.0, 9045.0, 60.57, 18.9, 0.0, 0.0, 0.0, 60.57, 60.57], + [1321.0, 9051.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1322.0, 9059.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1323.0, 9065.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1324.0, 9066.0, 23.26, 3.01, 0.0, 0.0, 0.0, 23.26, 23.26], + [1325.0, 9067.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1326.0, 9091.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1327.0, 9101.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1328.0, 9108.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1329.0, 9109.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1330.0, 9112.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1331.0, 9119.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1332.0, 9128.0, 50.56, 8.7, 0.0, 0.0, 0.0, 50.56, 50.56], + [1333.0, 9130.0, 245.51, 9.17, 0.0, 0.0, 0.0, 245.51, 245.51], + [1334.0, 9131.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1335.0, 9137.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1336.0, 9140.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1337.0, 9150.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1338.0, 9155.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1339.0, 9158.0, 54.96, 9.42, 0.0, 0.0, 0.0, 54.96, 54.96], + [1340.0, 9164.0, 7.71, 2.4, 0.0, 0.0, 0.0, 7.71, 7.71], + [1341.0, 9173.0, 66.07, 15.6, 0.0, 0.0, 0.0, 66.07, 66.07], + [1342.0, 9174.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1343.0, 9176.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1344.0, 9180.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [1345.0, 9181.0, 2.43, 1.35, 0.0, 0.0, 0.0, 2.43, 2.43], + [1346.0, 9185.0, 66.97, 18.6, 0.0, 0.0, 0.0, 66.97, 66.97], + [1347.0, 9189.0, 62.57, -61.0, 0.0, 0.0, 0.0, 62.57, 62.57], + [1348.0, 9191.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1349.0, 9203.0, 627.36, -73.13, 0.0, 0.0, 0.0, 627.36, 627.36], + [1350.0, 9213.0, -0.0, -0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1351.0, 9217.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0], + [1352.0, 9222.0, -5.15, -2.04, 0.0, 0.0, 0.0, -5.15, -5.15], + [1353.0, 9231.0, 242.08, 59.98, 0.0, 0.0, 0.0, 242.08, 242.08], + [1354.0, 9241.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]) + + self.real_params = True + super().__init__(*args, **kwargs) diff --git a/powergrid_case/transmission/Case14.py b/powergrid_case/transmission/Case14.py new file mode 100644 index 0000000000000000000000000000000000000000..0d9238ac1f0ad6a22313dd9224ff1e678c293434 --- /dev/null +++ b/powergrid_case/transmission/Case14.py @@ -0,0 +1,142 @@ +"""IEEE 14-bus system (MATPOWER case14) + +Data Source: MATPOWER case file `source_mfile/case14.m` +Base MVA: 100.0 MVA +Base kV: 69.0 kV (nominal; MATPOWER bus table uses 0 for baseKV) + +UC / economic columns on ``self.units`` match PowerZooJax ``create_case14()`` and are +regenerated from ``powerzoo/case/raw_cases/case14.json`` via +``python -m powerzoo.case.raw_cases.scuc_json_to_case_units`` (keep that script and JSON +in sync with the sibling ``powerzoojax/case/raw_cases/`` tree). + +All values are in standard MATPOWER units (MW, MVAr, p.u.) + + +Nodes (bus) columns: + id, type, Pd, Qd, Gs, Bs, Vm, Va, baseKV, Vmax, Vmin + - type: 1=PQ, 2=PV, 3=Slack + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - Gs/Bs: Shunt conductance/susceptance (MW/MVAr at V=1.0 p.u.) + - Vm: Voltage magnitude (p.u.) + - Va: Voltage angle (degrees) + - baseKV: Base voltage (kV) + - Vmax/Vmin: Voltage limits (p.u.) + +Units (generators) columns: + id, bus_id, Pg, Qg, Qmax, Qmin, Vg, mBase, status, Pmax, Pmin, mc_a, mc_b, mc_c, + p_max, p_min, type, ramp_up, ramp_down, init_start_up_cost, keep_time, + init_power, init_state, min_up_time, min_down_time, init_no_load_cost + - Pg/Qg: Active/Reactive power output (MW/MVAr) + - Qmax/Qmin: Reactive power limits (MVAr) + - Vg: Voltage setpoint (p.u.) + - mBase: Machine base (MVA) + - status: >0 in-service, <=0 out-of-service + - Pmax/Pmin: Active power limits (MW) + - mc_a/mc_b/mc_c: Marginal cost coefficients (quadratic) + +Lines (branches) columns: + id, from, to, r, x, b, rateA, ratio, angle, status, floor, cap + - r/x: Resistance/Reactance (p.u.) + - b: Line charging susceptance (p.u.) + - rateA: Long-term rating (MVA) + - ratio: Transformer tap ratio (0 for line) + - angle: Transformer phase shift (degrees) + - status: 1=in-service, 0=out-of-service + - floor/cap: Power flow limits (MW) + +Loads columns: + id, bus_id, Pd, Qd, mc_a, mc_b, mc_c, d_max, d_min + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - mc_a/mc_b/mc_c: Marginal utility coefficients + - d_max/d_min: Demand limits (MW) +""" +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case14(ClearCase): + GRID_TYPE = "transmission" + BUS_COUNT = 14 + VOLTAGE_LEVEL = "HV" + SOURCE = "MATPOWER" + DESCRIPTION = "IEEE 14-bus test system" + + def __init__(self, *args, **kwargs): + # System base values + self.baseMVA = 100.0 + # MATPOWER case14 has baseKV=0 on all buses; use a nominal kV for metadata. + self.baseKV = 69.0 + + # Node (bus) data + self.nodes = DataFrame( + ['id', 'type', 'Pd', 'Qd', 'Gs', 'Bs', 'Vm', 'Va', 'baseKV', 'Vmax', 'Vmin'], + [[1.0, 3.0, 0.0, 0.0, 0.0, 0.0, 1.06, 0.0, 0.0, 1.06, 0.94], + [2.0, 2.0, 21.7, 12.7, 0.0, 0.0, 1.045, -4.98, 0.0, 1.06, 0.94], + [3.0, 2.0, 94.2, 19.0, 0.0, 0.0, 1.01, -12.72, 0.0, 1.06, 0.94], + [4.0, 1.0, 47.8, -3.9, 0.0, 0.0, 1.019, -10.33, 0.0, 1.06, 0.94], + [5.0, 1.0, 7.6, 1.6, 0.0, 0.0, 1.02, -8.78, 0.0, 1.06, 0.94], + [6.0, 2.0, 11.2, 7.5, 0.0, 0.0, 1.07, -14.22, 0.0, 1.06, 0.94], + [7.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.062, -13.37, 0.0, 1.06, 0.94], + [8.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.09, -13.36, 0.0, 1.06, 0.94], + [9.0, 1.0, 29.5, 16.6, 0.0, 19.0, 1.056, -14.94, 0.0, 1.06, 0.94], + [10.0, 1.0, 9.0, 5.8, 0.0, 0.0, 1.051, -15.1, 0.0, 1.06, 0.94], + [11.0, 1.0, 3.5, 1.8, 0.0, 0.0, 1.057, -14.79, 0.0, 1.06, 0.94], + [12.0, 1.0, 6.1, 1.6, 0.0, 0.0, 1.055, -15.07, 0.0, 1.06, 0.94], + [13.0, 1.0, 13.5, 5.8, 0.0, 0.0, 1.05, -15.16, 0.0, 1.06, 0.94], + [14.0, 1.0, 14.9, 5.0, 0.0, 0.0, 1.036, -16.04, 0.0, 1.06, 0.94]]) + + # Generator (unit) data — UC columns aligned with Case118 / PowerZooJax case14 + self.units = DataFrame( + ['id', 'bus_id', 'Pg', 'Qg', 'Qmax', 'Qmin', 'Vg', 'mBase', 'status', + 'Pmax', 'Pmin', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min', + 'type', 'ramp_up', 'ramp_down', 'init_start_up_cost', 'keep_time', + 'init_power', 'init_state', 'min_up_time', 'min_down_time', 'init_no_load_cost'], + [[1.0, 1.0, 232.4, -16.9, 10.0, 0.0, 1.06, 100.0, 1.0, 332.4, 0.0, 0.0, 0.05541301, 34.216168, 332.4, 0.0, 'gas', 0.6953069, 0.6953069, 34238.45, 48.0, 230.74888, 1.0, 2.0, 2.0, 0.0], + [2.0, 2.0, 40.0, 42.4, 50.0, -40.0, 1.045, 100.0, 1.0, 140.0, 0.0, 0.00897295, -1.143378, 67.97416, 140.0, 0.0, 'gas', 0.66157144, 0.66157144, 11382.84, 48.0, 0.0, 0.0, 2.0, 2.0, 0.0], + [3.0, 3.0, 0.0, 23.4, 40.0, 0.0, 1.01, 100.0, 1.0, 100.0, 0.0, 0.0357393, -2.380081, 72.64597, 100.0, 0.0, 'gas', 0.6621, 0.6621, 5235.41, 48.0, 0.0, 0.0, 2.0, 2.0, 0.0], + [4.0, 6.0, 0.0, 12.2, 24.0, -6.0, 1.07, 100.0, 1.0, 100.0, 0.0, 0.03130176, -2.3915932, 78.5705, 100.0, 0.0, 'gas', 0.6694, 0.6694, 5272.29, 48.0, 0.0, 0.0, 8.0, 8.0, 0.0], + [5.0, 8.0, 0.0, 17.4, 24.0, -6.0, 1.09, 100.0, 1.0, 100.0, 0.0, 0.03348683, -2.4855613, 76.65385, 100.0, 0.0, 'gas', 0.6504, 0.6504, 7950.56, 48.0, 0.0, 0.0, 2.0, 2.0, 0.0]]) + + # Branch (line) data + self.lines = DataFrame( + ['id', 'from', 'to', 'r', 'x', 'b', 'rateA', 'ratio', 'angle', 'status', 'floor', 'cap'], + [[1.0, 1.0, 2.0, 0.01938, 0.05917, 0.0528, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [2.0, 1.0, 5.0, 0.05403, 0.22304, 0.0492, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [3.0, 2.0, 3.0, 0.04699, 0.19797, 0.0438, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [4.0, 2.0, 4.0, 0.05811, 0.17632, 0.034, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [5.0, 2.0, 5.0, 0.05695, 0.17388, 0.0346, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [6.0, 3.0, 4.0, 0.06701, 0.17103, 0.0128, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [7.0, 4.0, 5.0, 0.01335, 0.04211, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [8.0, 4.0, 7.0, 0.0, 0.20912, 0.0, 0.0, 0.978, 0.0, 1.0, 0.0, 0.0], + [9.0, 4.0, 9.0, 0.0, 0.55618, 0.0, 0.0, 0.969, 0.0, 1.0, 0.0, 0.0], + [10.0, 5.0, 6.0, 0.0, 0.25202, 0.0, 0.0, 0.932, 0.0, 1.0, 0.0, 0.0], + [11.0, 6.0, 11.0, 0.09498, 0.1989, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [12.0, 6.0, 12.0, 0.12291, 0.25581, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [13.0, 6.0, 13.0, 0.06615, 0.13027, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [14.0, 7.0, 8.0, 0.0, 0.17615, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [15.0, 7.0, 9.0, 0.0, 0.11001, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [16.0, 9.0, 10.0, 0.03181, 0.0845, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [17.0, 9.0, 14.0, 0.12711, 0.27038, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [18.0, 10.0, 11.0, 0.08205, 0.19207, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [19.0, 12.0, 13.0, 0.22092, 0.19988, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [20.0, 13.0, 14.0, 0.17093, 0.34802, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0]]) + + # Load data + self.loads = DataFrame( + ['id', 'bus_id', 'Pd', 'Qd', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2.0, 2.0, 21.7, 12.7, 0.0, 0.0, 0.0, 21.7, 21.7], + [3.0, 3.0, 94.2, 19.0, 0.0, 0.0, 0.0, 94.2, 94.2], + [4.0, 4.0, 47.8, -3.9, 0.0, 0.0, 0.0, 47.8, 47.8], + [5.0, 5.0, 7.6, 1.6, 0.0, 0.0, 0.0, 7.6, 7.6], + [6.0, 6.0, 11.2, 7.5, 0.0, 0.0, 0.0, 11.2, 11.2], + [7.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [8.0, 8.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [9.0, 9.0, 29.5, 16.6, 0.0, 0.0, 0.0, 29.5, 29.5], + [10.0, 10.0, 9.0, 5.8, 0.0, 0.0, 0.0, 9.0, 9.0], + [11.0, 11.0, 3.5, 1.8, 0.0, 0.0, 0.0, 3.5, 3.5], + [12.0, 12.0, 6.1, 1.6, 0.0, 0.0, 0.0, 6.1, 6.1], + [13.0, 13.0, 13.5, 5.8, 0.0, 0.0, 0.0, 13.5, 13.5], + [14.0, 14.0, 14.9, 5.0, 0.0, 0.0, 0.0, 14.9, 14.9]]) + + self.real_params = True + super().__init__(*args, **kwargs) diff --git a/powergrid_case/transmission/Case2383wp.py b/powergrid_case/transmission/Case2383wp.py new file mode 100644 index 0000000000000000000000000000000000000000..c648e794ed688930b82bd22f361748536bac1332 --- /dev/null +++ b/powergrid_case/transmission/Case2383wp.py @@ -0,0 +1,8069 @@ +"""Power System Case: 2383wp + +Data Source: MATPOWER case file +Base MVA: 100.0 MVA +Base kV: 220.0 kV + +All values are in standard MATPOWER units (MW, MVAr, p.u.) + + +Nodes (bus) columns: + id, type, Pd, Qd, Gs, Bs, Vm, Va, baseKV, Vmax, Vmin + - type: 1=PQ, 2=PV, 3=Slack + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - Gs/Bs: Shunt conductance/susceptance (MW/MVAr at V=1.0 p.u.) + - Vm: Voltage magnitude (p.u.) + - Va: Voltage angle (degrees) + - baseKV: Base voltage (kV) + - Vmax/Vmin: Voltage limits (p.u.) + +Units (generators) columns: + id, bus_id, Pg, Qg, Qmax, Qmin, Vg, mBase, status, Pmax, Pmin, mc_a, mc_b, mc_c + - Pg/Qg: Active/Reactive power output (MW/MVAr) + - Qmax/Qmin: Reactive power limits (MVAr) + - Vg: Voltage setpoint (p.u.) + - mBase: Machine base (MVA) + - status: >0 in-service, <=0 out-of-service + - Pmax/Pmin: Active power limits (MW) + - mc_a/mc_b/mc_c: Marginal cost coefficients (quadratic) + +Lines (branches) columns: + id, from, to, r, x, b, rateA, ratio, angle, status, floor, cap + - r/x: Resistance/Reactance (p.u.) + - b: Line charging susceptance (p.u.) + - rateA: Long-term rating (MVA) + - ratio: Transformer tap ratio (0 for line) + - angle: Transformer phase shift (degrees) + - status: 1=in-service, 0=out-of-service + - floor/cap: Power flow limits (MW) + +Loads columns: + id, bus_id, Pd, Qd, mc_a, mc_b, mc_c, d_max, d_min + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - mc_a/mc_b/mc_c: Marginal utility coefficients + - d_max/d_min: Demand limits (MW) +""" +from math import inf + +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case2383wp(ClearCase): + GRID_TYPE = "transmission" + BUS_COUNT = 2383 + VOLTAGE_LEVEL = "HV" + SOURCE = "MATPOWER" + DESCRIPTION = "Polish 2383-bus winter peak system" + + def __init__(self, *args, **kwargs): + # System base values + self.baseMVA = 100.0 + self.baseKV = 220.0 + + # Node (bus) data + self.nodes = DataFrame( + ['id', 'type', 'Pd', 'Qd', 'Gs', 'Bs', 'Vm', 'Va', 'baseKV', 'Vmax', 'Vmin'], + [[1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0945877, -1.4947677, 220.0, 1.11, 0.95], + [2.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0853611, -1.0101313, 220.0, 1.11, 0.95], + [3.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0745702, -26.208185, 220.0, 1.11, 0.95], + [4.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0714122, -8.5164763, 220.0, 1.11, 0.95], + [5.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0665303, -18.99745, 220.0, 1.11, 0.95], + [6.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0235863, -13.822343, 400.0, 1.05, 0.95], + [7.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0597742, -21.443703, 220.0, 1.11, 0.95], + [8.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0274658, -10.380289, 400.0, 1.05, 0.95], + [9.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0356969, -16.876105, 400.0, 1.05, 0.95], + [10.0, 2.0, 12.23, 9.0, 0.0, 0.0, 1.1082311, -20.649904, 220.0, 1.11, 0.95], + [11.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.077772, -7.0641396, 220.0, 1.11, 0.95], + [12.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0668445, -23.917665, 220.0, 1.11, 0.95], + [13.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0651982, -21.489714, 220.0, 1.11, 0.95], + [14.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0663588, -5.069768, 220.0, 1.11, 0.95], + [15.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0094205, -15.318814, 400.0, 1.05, 0.95], + [16.0, 2.0, 54.88, 100.0, 0.0, 0.0, 1.0974008, -0.98470838, 220.0, 1.11, 0.95], + [17.0, 2.0, 77.0, 150.0, 0.0, 0.0, 1.0910267, -0.14840674, 220.0, 1.11, 0.95], + [18.0, 3.0, 153.0, 350.0, 0.0, 0.0, 1.0337129, 0.0, 400.0, 1.05, 0.95], + [19.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0659295, -22.685677, 220.0, 1.11, 0.95], + [20.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0371271, -1.9368717, 400.0, 1.05, 0.95], + [21.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0594484, -21.874798, 220.0, 1.11, 0.95], + [22.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0814061, -12.38874, 220.0, 1.11, 0.95], + [23.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0623561, -16.684586, 220.0, 1.11, 0.95], + [24.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0544773, -12.101862, 220.0, 1.11, 0.95], + [25.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0566312, -10.623758, 220.0, 1.11, 0.95], + [26.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0514089, -19.520072, 220.0, 1.11, 0.95], + [27.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.065879, -10.248111, 220.0, 1.11, 0.95], + [28.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0658528, -10.243115, 220.0, 1.11, 0.95], + [29.0, 2.0, 25.98, 60.0, 0.0, 0.0, 1.0967104, -15.340069, 220.0, 1.11, 0.95], + [30.0, 2.0, 25.98, 60.0, 0.0, 0.0, 1.0967037, -15.340793, 220.0, 1.11, 0.95], + [31.0, 2.0, 20.98, 50.0, 0.0, 0.0, 1.0214422, -10.730991, 400.0, 1.05, 0.95], + [32.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0214388, -10.770221, 400.0, 1.05, 0.95], + [33.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0603418, -11.007759, 220.0, 1.11, 0.95], + [34.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0437449, -10.313949, 400.0, 1.05, 0.95], + [35.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0437713, -10.321962, 400.0, 1.05, 0.95], + [36.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0036235, -14.019908, 400.0, 1.05, 0.95], + [37.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0617538, -17.65358, 220.0, 1.11, 0.95], + [38.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0617576, -17.652543, 220.0, 1.11, 0.95], + [39.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0154269, -9.4424041, 400.0, 1.05, 0.95], + [40.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0154039, -9.4320741, 400.0, 1.05, 0.95], + [41.0, 2.0, 11.99, 30.0, 0.0, 0.0, 1.0608776, -8.4979859, 220.0, 1.11, 0.95], + [42.0, 2.0, 11.99, 30.0, 0.0, 0.0, 1.0608614, -8.5104656, 220.0, 1.11, 0.95], + [43.0, 2.0, 23.98, 60.0, 0.0, 0.0, 1.0229141, -6.9130429, 400.0, 1.05, 0.95], + [44.0, 2.0, 23.98, 60.0, 0.0, 0.0, 1.0229414, -6.9257613, 400.0, 1.05, 0.95], + [45.0, 2.0, 159.84, 75.0, 0.0, 0.0, 1.0792177, -16.289871, 220.0, 1.11, 0.95], + [46.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0792304, -16.288302, 220.0, 1.11, 0.95], + [47.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0601105, -10.892212, 220.0, 1.11, 0.95], + [48.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0778118, -15.293456, 220.0, 1.11, 0.95], + [49.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0778399, -15.297932, 220.0, 1.11, 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0.95], + [2320.0, 1.0, 8.99, 2.3, 0.0, 0.0, 1.0207365, -35.856756, 110.0, 1.12, 0.95], + [2321.0, 1.0, 8.99, 0.4, 0.0, 0.0, 1.0841969, -35.069976, 110.0, 1.12, 0.95], + [2322.0, 1.0, 8.99, 0.5, 0.0, 0.0, 1.0822632, -34.4275, 110.0, 1.12, 0.95], + [2323.0, 2.0, 24.98, 3.0, 0.0, 0.0, 1.0808472, -34.968375, 110.0, 1.12, 0.95], + [2324.0, 1.0, 8.49, 4.3, 0.0, 0.0, 1.0718074, -31.529234, 110.0, 1.12, 0.95], + [2325.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0760246, -31.362847, 110.0, 1.12, 0.95], + [2326.0, 1.0, 24.68, 5.0, 0.0, 0.0, 1.0644052, -32.395798, 110.0, 1.12, 0.95], + [2327.0, 1.0, 0.5, 0.2, 0.0, 0.0, 1.06762, -32.122395, 110.0, 1.12, 0.95], + [2328.0, 2.0, 29.98, 4.8, 0.0, 0.0, 1.0359467, -35.096288, 110.0, 1.12, 0.95], + [2329.0, 1.0, 11.99, 2.0, 0.0, 0.0, 1.079157, -35.134404, 110.0, 1.12, 0.95], + [2330.0, 2.0, 0.4, 0.1, 0.0, 0.0, 1.0694516, -31.77017, 110.0, 1.12, 0.95], + [2331.0, 1.0, 20.98, 3.0, 0.0, 0.0, 1.0658079, -30.718951, 110.0, 1.12, 0.95], + [2332.0, 1.0, 4.8, 1.0, 0.0, 0.0, 1.0747609, -31.593112, 110.0, 1.12, 0.95], + [2333.0, 1.0, 5.3, 1.0, 0.0, 0.0, 1.091551, -22.517637, 110.0, 1.12, 0.95], + [2334.0, 1.0, 7.99, 2.4, 0.0, 0.0, 1.0552913, -33.116107, 110.0, 1.12, 0.95], + [2335.0, 1.0, 6.5, 3.0, 0.0, 0.0, 1.0641083, -33.037799, 110.0, 1.12, 0.95], + [2336.0, 2.0, 68.93, 43.0, 0.0, 0.0, 1.0745781, -29.915079, 110.0, 1.12, 0.95], + [2337.0, 1.0, 6.5, 2.5, 0.0, 0.0, 1.0889328, -30.626306, 110.0, 1.12, 0.95], + [2338.0, 1.0, 22.98, 4.6, 0.0, 0.0, 1.0583228, -32.911792, 110.0, 1.12, 0.95], + [2339.0, 2.0, 34.97, 6.5, 0.0, 0.0, 1.0700813, -31.398646, 110.0, 1.12, 0.95], + [2340.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0701039, -31.396656, 110.0, 1.12, 0.95], + [2341.0, 1.0, 5.1, 1.2, 0.0, 0.0, 1.0753497, -31.559337, 110.0, 1.12, 0.95], + [2342.0, 1.0, 15.49, 5.2, 0.0, 0.0, 1.0665995, -31.653852, 110.0, 1.12, 0.95], + [2343.0, 1.0, 23.58, 7.1, 0.0, 0.0, 1.0672554, -31.573076, 110.0, 1.12, 0.95], + [2344.0, 1.0, 12.09, 0.0, 0.0, 0.0, 1.0605578, -32.110542, 110.0, 1.12, 0.95], + [2345.0, 1.0, 17.49, 4.9, 0.0, 0.0, 1.0593761, -31.932342, 110.0, 1.12, 0.95], + [2346.0, 1.0, 9.99, 2.7, 0.0, 0.0, 1.0705361, -27.651853, 110.0, 1.12, 0.95], + [2347.0, 1.0, 18.19, 5.3, 0.0, 0.0, 1.0656839, -31.701924, 110.0, 1.12, 0.95], + [2348.0, 1.0, 12.49, 3.8, 0.0, 0.0, 1.0198084, -34.069725, 110.0, 1.12, 0.95], + [2349.0, 1.0, 8.29, 3.9, 0.0, 0.0, 1.0636052, -31.893292, 110.0, 1.12, 0.95], + [2350.0, 1.0, 11.99, 1.0, 0.0, 0.0, 1.0772393, -35.686239, 110.0, 1.12, 0.95], + [2351.0, 1.0, 8.79, 0.0, 0.0, 0.0, 1.0954645, -34.962188, 110.0, 1.12, 0.95], + [2352.0, 1.0, 18.49, 6.2, 0.0, 0.0, 1.0670838, -30.222895, 110.0, 1.12, 0.95], + [2353.0, 1.0, 21.98, 4.6, 0.0, 0.0, 1.1042369, -29.650834, 110.0, 1.12, 0.95], + [2354.0, 1.0, 19.59, 4.4, 0.0, 0.0, 1.1008499, -29.695343, 110.0, 1.12, 0.95], + [2355.0, 1.0, 8.99, 0.3, 0.0, 0.0, 1.1100473, -30.405814, 110.0, 1.12, 0.95], + [2356.0, 1.0, 19.19, 4.3, 0.0, 0.0, 1.0692879, -32.101777, 110.0, 1.12, 0.95], + [2357.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0916163, -29.174648, 110.0, 1.12, 0.95], + [2358.0, 1.0, 4.1, 2.0, 0.0, 0.0, 1.0916018, -29.174942, 110.0, 1.12, 0.95], + [2359.0, 1.0, 12.49, 4.5, 0.0, 0.0, 1.0628662, -32.26635, 110.0, 1.12, 0.95], + [2360.0, 1.0, 22.78, 7.9, 0.0, 0.0, 1.0805571, -29.463386, 110.0, 1.12, 0.95], + [2361.0, 2.0, 18.59, 5.7, 0.0, 0.0, 1.0834723, -29.106835, 110.0, 1.12, 0.95], + [2362.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.083454, -29.108701, 110.0, 1.12, 0.95], + [2363.0, 1.0, 23.38, 5.9, 0.0, 0.0, 1.0821686, -29.515995, 110.0, 1.12, 0.95], + [2364.0, 1.0, 6.5, 0.5, 0.0, 0.0, 1.0648545, -32.408644, 110.0, 1.12, 0.95], + [2365.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0720275, -31.400049, 110.0, 1.12, 0.95], + [2366.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0811816, -35.567389, 110.0, 1.12, 0.95], + [2367.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0648735, -32.406542, 110.0, 1.12, 0.95], + [2368.0, 1.0, 32.98, 6.0, 0.0, 0.0, 1.0794752, -30.054477, 110.0, 1.12, 0.95], + [2369.0, 1.0, 2.0, 1.0, 0.0, 0.0, 1.0795552, -30.033595, 110.0, 1.12, 0.95], + [2370.0, 1.0, 11.49, 2.7, 0.0, 0.0, 1.0716062, -31.465081, 110.0, 1.12, 0.95], + [2371.0, 1.0, 12.99, 3.3, 0.0, 0.0, 1.0734793, -31.384206, 110.0, 1.12, 0.95], + [2372.0, 2.0, 49.95, 13.0, 0.0, 0.0, 1.0901753, -29.261172, 110.0, 1.12, 0.95], + [2373.0, 1.0, 39.97, 13.0, 0.0, 0.0, 1.0901634, -29.263099, 110.0, 1.12, 0.95], + [2374.0, 1.0, 9.59, 1.2, 0.0, 0.0, 1.0178542, -39.165348, 110.0, 1.12, 0.95], + [2375.0, 1.0, 10.99, 5.0, 0.0, 0.0, 1.0640798, -34.319506, 110.0, 1.12, 0.95], + [2376.0, 2.0, 21.98, 4.8, 0.0, 0.0, 1.0425808, -27.572248, 110.0, 1.12, 0.95], + [2377.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.1199873, -28.177197, 110.0, 1.12, 0.95], + [2378.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.12, -28.175349, 110.0, 1.12, 0.95], + [2379.0, 2.0, 12.99, 6.5, 0.0, 0.0, 1.0535756, -32.447533, 110.0, 1.12, 0.95], + [2380.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0964598, -33.305123, 110.0, 1.12, 0.95], + [2381.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0964544, -33.305306, 110.0, 1.12, 0.95], + [2382.0, 1.0, 3.0, 0.4, 0.0, 0.0, 1.0939913, -33.633139, 110.0, 1.12, 0.95], + [2383.0, 1.0, 50.0, 20.0, 0.0, 0.0, 1.0968483, -30.102203, 110.0, 1.12, 0.95]]) + + # Generator (unit) data + self.units = DataFrame( + ['id', 'bus_id', 'Pg', 'Qg', 'Qmax', 'Qmin', 'Vg', 'mBase', 'status', 'Pmax', 'Pmin', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min'], + [[1.0, 10.0, 400.0, 120.0, 120.0, 0.0, 1.0, 168.0, 1.0, 400.0, 70.0, 0.0, 0.0, 117.95, 400.0, 70.0], + [2.0, 16.0, 720.0, 160.532, 440.0, -40.0, 1.0, 823.0, 1.0, 720.0, 120.0, 0.0, 0.0, 48.89, 720.0, 120.0], + [3.0, 17.0, 1080.0, 212.82, 660.0, -60.0, 1.0, 1234.0, 1.0, 1080.0, 120.0, 0.0, 0.0, 98.47, 1080.0, 120.0], + [4.0, 18.0, 2520.0, 160.59, 1540.0, -140.0, 1.0, 2879.0, 1.0, 2520.0, 120.0, 0.0, 0.0, 128.73, 2520.0, 120.0], + [5.0, 29.0, 70.0, 240.0, 240.0, 0.0, 1.0, 511.0, 1.0, 400.0, 70.0, 0.0, 0.0, 158.23, 400.0, 70.0], + [6.0, 30.0, 70.0, 129.949, 240.0, 0.0, 1.0, 511.0, 1.0, 800.0, 70.0, 0.0, 0.0, 165.62, 800.0, 70.0], + [7.0, 31.0, 1000.0, 0.0, 350.0, 0.0, 1.0, 420.0, 1.0, 1000.0, 150.0, 0.0, 0.0, 71.22, 1000.0, 150.0], + [8.0, 41.0, 200.0, 0.0, 120.0, 0.0, 1.0, 241.0, 1.0, 200.0, 70.0, 0.0, 0.0, 102.25, 200.0, 70.0], + [9.0, 42.0, 70.0, 0.0, 120.0, 0.0, 1.0, 241.0, 1.0, 410.0, 70.0, 0.0, 0.0, 147.83, 410.0, 70.0], + [10.0, 43.0, 410.0, 0.0, 240.0, 0.0, 1.0, 482.0, 1.0, 410.0, 70.0, 0.0, 0.0, 75.37, 410.0, 70.0], + [11.0, 44.0, 410.0, 0.0, 240.0, 0.0, 1.0, 482.0, 1.0, 410.0, 70.0, 0.0, 0.0, 86.01, 410.0, 70.0], + [12.0, 45.0, 42.2, 21.0, 21.0, 0.0, 1.0, 49.0, 1.0, 42.2, 39.14, 0.0, 0.0, 0.0, 42.2, 39.14], + [13.0, 63.0, 650.0, 103.63, 302.0, 0.0, 1.0, 473.0, 1.0, 650.0, 145.0, 0.0, 0.0, 68.74, 650.0, 145.0], + [14.0, 64.0, 450.0, 78.8702, 311.0, 2.0, 1.0, 475.0, 1.0, 450.0, 145.0, 0.0, 0.0, 81.91, 450.0, 145.0], + [15.0, 67.0, 750.0, 413.726, 449.0, 0.0, 1.0, 864.0, 1.0, 750.0, 220.0, 0.0, 0.0, 81.88, 750.0, 220.0], + [16.0, 83.0, 225.0, -89.0, 190.0, -89.0, 1.0, 239.0, 1.0, 225.0, 140.0, 0.0, 0.0, 58.78, 225.0, 140.0], + [17.0, 84.0, 225.0, 167.231, 190.0, -89.0, 1.0, 251.0, 1.0, 225.0, 140.0, 0.0, 0.0, 85.57, 225.0, 140.0], + [18.0, 85.0, 120.0, 119.623, 125.0, -50.0, 1.0, 133.0, 1.0, 120.0, 40.0, 0.0, 0.0, 101.38, 120.0, 40.0], + [19.0, 86.0, 120.0, -6.01871, 125.0, -50.0, 1.0, 133.0, 1.0, 120.0, 40.0, 0.0, 0.0, 122.43, 120.0, 40.0], + [20.0, 93.0, 120.0, 50.5085, 90.0, 5.0, 1.0, 123.0, 1.0, 120.0, 80.0, 0.0, 0.0, 96.62, 120.0, 80.0], + [21.0, 95.0, 110.0, 27.0, 68.0, 27.0, 1.0, 105.0, 1.0, 110.0, 50.0, 0.0, 0.0, 106.73, 110.0, 50.0], + [22.0, 97.0, 87.6, 41.8528, 68.0, 27.0, 1.0, 105.0, 1.0, 87.6, 83.26, 0.0, 0.0, 0.0, 87.6, 83.26], + [23.0, 103.0, 160.0, 68.7599, 177.0, -82.0, 1.0, 239.0, 1.0, 400.0, 160.0, 0.0, 0.0, 151.94, 400.0, 160.0], + [24.0, 104.0, 225.0, 97.3097, 379.0, -177.0, 1.0, 490.0, 1.0, 225.0, 140.0, 0.0, 0.0, 107.51, 225.0, 140.0], + [25.0, 105.0, 430.0, -165.0, 353.0, -165.0, 1.0, 502.0, 1.0, 430.0, 160.0, 0.0, 0.0, 103.53, 430.0, 160.0], + [26.0, 109.0, 250.0, 17.6233, 65.0, 0.0, 1.0, 277.0, 1.0, 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0.0, 2.4, 2.28], + [308.0, 2272.0, 10.0, 4.0, 4.0, 0.0, 1.0, 12.0, 1.0, 10.0, 9.5, 0.0, 0.0, 0.0, 10.0, 9.5], + [309.0, 2273.0, 6.3, 2.0, 2.0, 0.0, 1.0, 8.0, 1.0, 6.3, 5.99, 0.0, 0.0, 0.0, 6.3, 5.99], + [310.0, 2278.0, 1.5, 0.0, 0.0, 0.0, 1.0, 2.0, 1.0, 1.5, 1.43, 0.0, 0.0, 0.0, 1.5, 1.43], + [311.0, 2290.0, 0.2, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.2, 0.19, 0.0, 0.0, 0.0, 0.2, 0.19], + [312.0, 2293.0, 2.5, 1.0, 1.0, 0.0, 1.0, 3.0, 1.0, 2.5, 2.38, 0.0, 0.0, 0.0, 2.5, 2.38], + [313.0, 2294.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.95, 0.0, 0.0, 0.0, 1.0, 0.95], + [314.0, 2296.0, 13.5, 4.0, 4.0, 0.0, 1.0, 16.0, 1.0, 13.5, 12.83, 0.0, 0.0, 0.0, 13.5, 12.83], + [315.0, 2298.0, 0.4, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 0.4, 0.38, 0.0, 0.0, 0.0, 0.4, 0.38], + [316.0, 2307.0, 0.4, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 0.4, 0.38, 0.0, 0.0, 0.0, 0.4, 0.38], + [317.0, 2323.0, 1.1, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.1, 1.05, 0.0, 0.0, 0.0, 1.1, 1.05], + [318.0, 2328.0, 3.0, 1.0, 1.0, 0.0, 1.0, 4.0, 1.0, 3.0, 2.85, 0.0, 0.0, 0.0, 3.0, 2.85], + [319.0, 2330.0, 0.3, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.3, 0.29, 0.0, 0.0, 0.0, 0.3, 0.29], + [320.0, 2336.0, 55.0, 41.0, 41.0, 0.0, 1.0, 66.0, 1.0, 55.0, 52.25, 0.0, 0.0, 0.0, 55.0, 52.25], + [321.0, 2339.0, 17.0, 6.0, 6.0, 0.0, 1.0, 20.0, 1.0, 17.0, 16.15, 0.0, 0.0, 0.0, 17.0, 16.15], + [322.0, 2361.0, 51.0, 10.0, 10.0, 0.0, 1.0, 61.0, 1.0, 51.0, 48.45, 0.0, 0.0, 0.0, 51.0, 48.45], + [323.0, 2372.0, 37.0, 19.0, 19.0, 0.0, 1.0, 44.0, 1.0, 37.0, 35.15, 0.0, 0.0, 0.0, 37.0, 35.15], + [324.0, 2376.0, 2.0, 1.0, 1.0, 0.0, 1.0, 2.0, 1.0, 2.0, 1.9, 0.0, 0.0, 0.0, 2.0, 1.9], + [325.0, 2379.0, 7.0, 2.0, 2.0, 0.0, 1.0, 8.0, 1.0, 7.0, 6.65, 0.0, 0.0, 0.0, 7.0, 6.65], + [326.0, 2380.0, 50.0, -18.0, 22.0, -18.0, 1.0, 60.0, 1.0, 50.0, 47.5, 0.0, 0.0, 0.0, 50.0, 47.5], + [327.0, 2381.0, 50.0, -13.4913, 22.0, -18.0, 1.0, 60.0, 1.0, 50.0, 47.5, 0.0, 0.0, 0.0, 50.0, 47.5]]) + + # Branch (line) data + self.lines = DataFrame( + ['id', 'from', 'to', 'r', 'x', 'b', 'rateA', 'ratio', 'angle', 'status', 'floor', 'cap'], + [[1.0, 16.0, 1.0, 0.00155, 0.01169, 0.0182, 160.0, 0.0, 0.0, 1.0, -160.0, 160.0], + [2.0, 355.0, 1.0, 0.00157, 0.06612, 0.0, 160.0, 1.0099, 0.0, 1.0, -160.0, 160.0], + [3.0, 17.0, 2.0, 0.00155, 0.01169, 0.0182, 160.0, 0.0, 0.0, 1.0, -160.0, 160.0], + [4.0, 354.0, 2.0, 0.00157, 0.06612, 0.0, 160.0, 1.022, 0.0, 1.0, -160.0, 160.0], + [5.0, 10.0, 3.0, 0.01068, 0.07895, 0.1226, 274.0, 0.0, 0.0, 1.0, -274.0, 274.0], + [6.0, 219.0, 3.0, 0.00165, 0.06736, 0.0, 160.0, 1.027, 0.0, 1.0, -160.0, 160.0], + [7.0, 220.0, 3.0, 0.00165, 0.06736, 0.0, 160.0, 0.9955, 0.0, 1.0, -160.0, 160.0], + [8.0, 7.0, 4.0, 0.01674, 0.09711, 0.14423, 377.0, 0.0, 0.0, 1.0, -377.0, 377.0], + [9.0, 11.0, 4.0, 0.00293, 0.01599, 0.02478, 335.0, 0.0, 0.0, 1.0, -335.0, 335.0], + [10.0, 14.0, 4.0, 0.00442, 0.03223, 0.04985, 464.0, 0.0, 0.0, 1.0, -464.0, 464.0], + [11.0, 16.0, 4.0, 0.00888, 0.06665, 0.08896, 377.0, 0.0, 0.0, 1.0, -377.0, 377.0], + [12.0, 22.0, 4.0, 0.00783, 0.043, 0.04962, 350.0, 0.0, 0.0, 1.0, -350.0, 350.0], + [13.0, 245.0, 4.0, 0.00165, 0.06901, 0.0, 160.0, 1.0594, 0.0, 1.0, -160.0, 160.0], + [14.0, 246.0, 4.0, 0.00165, 0.06901, 0.0, 160.0, 1.0448, 0.0, 1.0, -160.0, 160.0], + [15.0, 5.0, 6.0, 0.00064, 0.0305, 0.0, 400.0, 1.0435, 0.6, 1.0, -400.0, 400.0], + [16.0, 7.0, 5.0, 0.00525, 0.03988, 0.06195, 381.0, 0.0, 0.0, 1.0, -381.0, 381.0], + [17.0, 10.0, 5.0, 0.01459, 0.11219, 0.16553, 381.0, 0.0, 0.0, 1.0, -381.0, 381.0], + [18.0, 309.0, 5.0, 0.00165, 0.0686, 0.0, 160.0, 1.0646, 0.0, 1.0, -160.0, 160.0], + [19.0, 309.0, 5.0, 0.00165, 0.0686, 0.0, 160.0, 1.0523, 0.0, 1.0, -160.0, 160.0], + [20.0, 6.0, 8.0, 0.00112, 0.01329, 0.34125, 1316.0, 0.0, 0.0, 1.0, -1316.0, 1316.0], + [21.0, 6.0, 9.0, 0.00299, 0.03675, 0.9184, 1427.0, 0.0, 0.0, 1.0, -1427.0, 1427.0], + [22.0, 15.0, 6.0, 0.00298, 0.03417, 0.93504, 1427.0, 0.0, 0.0, 1.0, -1427.0, 1427.0], + [23.0, 31.0, 6.0, 0.0015, 0.01506, 0.4032, 1385.0, 0.0, 0.0, 1.0, -1385.0, 1385.0], + [24.0, 310.0, 6.0, 0.0015, 0.06188, 0.0, 250.0, 1.0613, 0.0, 1.0, -250.0, 250.0], + [25.0, 12.0, 7.0, 0.01211, 0.08742, 0.14017, 381.0, 0.0, 0.0, 1.0, -381.0, 381.0], + [26.0, 13.0, 7.0, 0.00205, 0.01326, 0.02243, 335.0, 0.0, 0.0, 1.0, -335.0, 335.0], + [27.0, 19.0, 7.0, 0.0057, 0.0407, 0.06021, 323.0, 0.0, 0.0, 1.0, -323.0, 323.0], + [28.0, 21.0, 7.0, 0.00093, 0.00651, 0.01113, 160.0, 0.0, 0.0, 1.0, -160.0, 160.0], + [29.0, 29.0, 7.0, 0.01269, 0.07498, 0.1302, 362.0, 0.0, 0.0, 1.0, -362.0, 362.0], + [30.0, 321.0, 7.0, 0.00041, 0.03368, 0.0, 250.0, 1.0323, 0.0, 1.0, -250.0, 250.0], + [31.0, 322.0, 7.0, 0.00165, 0.06775, 0.0, 160.0, 1.0569, 0.0, 1.0, -160.0, 160.0], + [32.0, 8.0, 18.0, 0.00336, 0.03977, 1.02163, 1316.0, 0.0, 0.0, 1.0, -1316.0, 1316.0], + [33.0, 332.0, 9.0, 0.00087, 0.05244, -0.02144, 330.0, 1.0781, 0.0, 1.0, -330.0, 330.0], + [34.0, 171.0, 10.0, 0.01409, 0.10413, 0.15972, 464.0, 0.0, 0.0, 1.0, -464.0, 464.0], + [35.0, 346.0, 10.0, 0.00124, 0.06839, 0.0, 160.0, 1.0054, 0.0, 1.0, -160.0, 160.0], + [36.0, 347.0, 10.0, 0.00124, 0.06839, 0.0, 160.0, 1.024, 0.0, 1.0, -160.0, 160.0], + [37.0, 16.0, 11.0, 0.0057, 0.03952, 0.07553, 464.0, 0.0, 0.0, 1.0, -464.0, 464.0], + [38.0, 17.0, 11.0, 0.0057, 0.03952, 0.07553, 464.0, 0.0, 0.0, 1.0, -464.0, 464.0], + [39.0, 111.0, 11.0, 0.01068, 0.06196, 0.09496, 394.0, 0.0, 0.0, 1.0, -394.0, 394.0], + [40.0, 352.0, 11.0, 0.00165, 0.06901, 0.0, 160.0, 1.0412, 0.0, 1.0, -160.0, 160.0], + [41.0, 353.0, 11.0, 0.00165, 0.06901, 0.0, 160.0, 1.0559, 0.0, 1.0, -160.0, 160.0], + [42.0, 140.0, 12.0, 0.01465, 0.10589, 0.17085, 464.0, 0.0, 0.0, 1.0, -464.0, 464.0], + [43.0, 359.0, 12.0, 0.00155, 0.06612, 0.0, 160.0, 1.0395, 0.0, 1.0, -160.0, 160.0], + [44.0, 360.0, 12.0, 0.00157, 0.06612, 0.0, 160.0, 1.059, 0.0, 1.0, -160.0, 160.0], + [45.0, 29.0, 13.0, 0.01345, 0.08114, 0.14113, 339.0, 0.0, 0.0, 1.0, -339.0, 339.0], + [46.0, 365.0, 13.0, 0.00165, 0.06901, 0.0, 160.0, 1.0312, 0.0, 1.0, -160.0, 160.0], + [47.0, 366.0, 13.0, 0.00165, 0.06901, 0.0, 160.0, 0.9872, 0.0, 1.0, -160.0, 160.0], + [48.0, 17.0, 14.0, 0.00384, 0.02853, 0.04588, 464.0, 0.0, 0.0, 1.0, -464.0, 464.0], + [49.0, 367.0, 14.0, 0.00157, 0.06798, 0.0, 160.0, 1.0664, 0.0, 1.0, -160.0, 160.0], + [50.0, 368.0, 14.0, 0.00165, 0.06901, 0.0, 160.0, 1.0777, 0.0, 1.0, -160.0, 160.0], + [51.0, 18.0, 15.0, 0.00358, 0.04262, 1.0944, 1662.0, 0.0, 0.0, 1.0, -1662.0, 1662.0], + [52.0, 15.0, 165.0, 0.00207, 0.02474, 0.664, 831.0, 0.0, 0.0, 1.0, -831.0, 831.0], + [53.0, 374.0, 15.0, 0.0015, 0.06188, 0.0, 250.0, 1.1502, 0.0, 1.0, -250.0, 250.0], + [54.0, 16.0, 18.0, 0.00036, 0.02519, 0.0, 500.0, 1.0605, 0.0, 1.0, -500.0, 500.0], + [55.0, 16.0, 73.0, 0.00909, 0.0624, 0.11142, 464.0, 0.0, 0.0, 1.0, -464.0, 464.0], + [56.0, 17.0, 18.0, 0.00036, 0.02519, 0.0, 500.0, 1.0607, 0.0, 1.0, -500.0, 500.0], + [57.0, 17.0, 74.0, 0.00868, 0.06405, 0.09699, 464.0, 0.0, 0.0, 1.0, -464.0, 464.0], + [58.0, 20.0, 18.0, 0.00063, 0.00749, 0.39226, 1427.0, 0.0, 0.0, 1.0, -1427.0, 1427.0], + [59.0, 75.0, 18.0, 0.00219, 0.02369, 0.59584, 1434.0, 0.0, 0.0, 1.0, -1434.0, 1434.0], + [60.0, 18.0, 76.0, 0.00137, 0.01625, 0.41184, 1662.0, 0.0, 0.0, 1.0, -1662.0, 1662.0], + [61.0, 18.0, 101.0, 0.00231, 0.02769, 0.70144, 1662.0, 0.0, 0.0, 1.0, -1662.0, 1662.0], + [62.0, 124.0, 19.0, 0.01696, 0.12366, 0.19699, 464.0, 0.0, 0.0, 1.0, -464.0, 464.0], + [63.0, 425.0, 19.0, 0.00165, 0.06818, 0.0, 160.0, 1.0241, 0.0, 1.0, -160.0, 160.0], + [64.0, 67.0, 20.0, 0.00331, 0.03425, 0.85888, 831.0, 0.0, 0.0, 1.0, -831.0, 831.0], + [65.0, 447.0, 20.0, 0.00137, 0.06119, -0.01504, 250.0, 1.0796, 0.0, 1.0, -250.0, 250.0], + [66.0, 448.0, 20.0, 0.00137, 0.06119, -0.01504, 250.0, 1.0923, 0.0, 1.0, -250.0, 250.0], + [67.0, 502.0, 21.0, 0.00165, 0.07107, 0.0, 160.0, 0.9922, 0.0, 1.0, -160.0, 160.0], + [68.0, 112.0, 22.0, 0.00465, 0.02618, 0.02962, 362.0, 0.0, 0.0, 1.0, -362.0, 362.0], + [69.0, 526.0, 22.0, 0.00165, 0.06901, 0.0, 160.0, 1.0685, 0.0, 1.0, -160.0, 160.0], + [70.0, 527.0, 22.0, 0.00165, 0.06901, 0.0, 160.0, 1.0424, 0.0, 1.0, -160.0, 160.0], + [71.0, 37.0, 23.0, 0.01163, 0.07031, 0.1058, 394.0, 0.0, 0.0, 1.0, -394.0, 394.0], + [72.0, 46.0, 23.0, 0.00837, 0.04868, 0.07348, 457.0, 0.0, 0.0, 1.0, -457.0, 457.0], + [73.0, 53.0, 23.0, 0.01122, 0.06558, 0.09835, 274.0, 0.0, 0.0, 1.0, -274.0, 274.0], + [74.0, 540.0, 23.0, 0.0014, 0.0668, 0.0, 160.0, 1.0182, 0.0, 1.0, -160.0, 160.0], + [75.0, 54.0, 24.0, 0.00769, 0.05727, 0.08789, 160.0, 0.0, 0.0, 1.0, -160.0, 160.0], + [76.0, 545.0, 24.0, 0.00151, 0.06715, 0.0, 160.0, 1.0161, 0.0, 1.0, -160.0, 160.0], + [77.0, 41.0, 25.0, 0.00556, 0.04145, 0.0636, 274.0, 0.0, 0.0, 1.0, -274.0, 274.0], + [78.0, 53.0, 25.0, 0.00452, 0.03368, 0.05169, 464.0, 0.0, 0.0, 1.0, -464.0, 464.0], + [79.0, 54.0, 25.0, 0.00019, 0.0014, 0.00213, 464.0, 0.0, 0.0, 1.0, -464.0, 464.0], + [80.0, 564.0, 25.0, 0.00157, 0.07808, 0.0, 160.0, 1.0276, 0.0, 1.0, -160.0, 160.0], + [81.0, 38.0, 26.0, 0.00698, 0.05196, 0.07967, 160.0, 0.0, 0.0, 1.0, -160.0, 160.0], + 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78.0], + [2870.0, 2323.0, 2380.0, 0.07306, 0.1919, 0.01832, 68.0, 0.0, 0.0, 1.0, -68.0, 68.0], + [2871.0, 2359.0, 2324.0, 0.02017, 0.05223, 0.00545, 120.0, 0.0, 0.0, 1.0, -120.0, 120.0], + [2872.0, 2324.0, 2379.0, 0.03562, 0.10942, 0.01146, 68.0, 0.0, 0.0, 1.0, -68.0, 68.0], + [2873.0, 2326.0, 2367.0, 0.00525, 0.0165, 0.00163, 114.0, 0.0, 0.0, 1.0, -114.0, 114.0], + [2874.0, 2340.0, 2339.0, 0.0, 0.0001, 0.0, 438.0, 0.0, 0.0, 1.0, -438.0, 438.0], + [2875.0, 2342.0, 2339.0, 0.00421, 0.01355, 0.0014, 131.0, 0.0, 0.0, 1.0, -131.0, 131.0], + [2876.0, 2343.0, 2339.0, 0.00306, 0.00992, 0.00102, 114.0, 0.0, 0.0, 1.0, -114.0, 114.0], + [2877.0, 2342.0, 2343.0, 0.00554, 0.01793, 0.00184, 137.0, 0.0, 0.0, 1.0, -137.0, 137.0], + [2878.0, 2344.0, 2342.0, 0.01777, 0.05736, 0.00588, 137.0, 0.0, 0.0, 1.0, -137.0, 137.0], + [2879.0, 2347.0, 2342.0, 0.00496, 0.00744, 0.00073, 114.0, 0.0, 0.0, 1.0, -114.0, 114.0], + [2880.0, 2347.0, 2342.0, 0.00992, 0.03488, 0.00407, 76.0, 0.0, 0.0, 1.0, -76.0, 76.0], + [2881.0, 2348.0, 2379.0, 0.08653, 0.11405, 0.01019, 57.0, 0.0, 0.0, 1.0, -57.0, 57.0], + [2882.0, 2350.0, 2366.0, 0.01686, 0.05427, 0.00558, 68.0, 0.0, 0.0, 1.0, -68.0, 68.0], + [2883.0, 2353.0, 2378.0, 0.02306, 0.07438, 0.00765, 137.0, 0.0, 0.0, 1.0, -137.0, 137.0], + [2884.0, 2354.0, 2377.0, 0.01736, 0.05686, 0.00578, 137.0, 0.0, 0.0, 1.0, -137.0, 137.0], + [2885.0, 2358.0, 2357.0, 0.0, 0.0001, 0.0, 438.0, 0.0, 0.0, 1.0, -438.0, 438.0], + [2886.0, 2357.0, 2363.0, 0.01504, 0.04132, 0.00426, 90.0, 0.0, 0.0, 1.0, -90.0, 90.0], + [2887.0, 2357.0, 2372.0, 0.00496, 0.00744, 0.00073, 114.0, 0.0, 0.0, 1.0, -114.0, 114.0], + [2888.0, 2357.0, 2372.0, 0.00496, 0.00744, 0.00073, 114.0, 0.0, 0.0, 1.0, -114.0, 114.0], + [2889.0, 2358.0, 2361.0, 0.01843, 0.06, 0.00615, 137.0, 0.0, 0.0, 1.0, -137.0, 137.0], + [2890.0, 2363.0, 2360.0, 0.00934, 0.01653, 0.00174, 90.0, 0.0, 0.0, 1.0, -90.0, 90.0], + [2891.0, 2362.0, 2361.0, 0.0, 0.0001, 0.0, 438.0, 0.0, 0.0, 1.0, -438.0, 438.0], + [2892.0, 2364.0, 2367.0, 0.00026, 0.00066, 7e-05, 114.0, 0.0, 0.0, 1.0, -114.0, 114.0], + [2893.0, 2373.0, 2372.0, 0.0, 0.0001, 0.0, 438.0, 0.0, 0.0, 1.0, -438.0, 438.0], + [2894.0, 2378.0, 2377.0, 0.0, 0.0001, 0.0, 438.0, 0.0, 0.0, 1.0, -438.0, 438.0], + [2895.0, 2381.0, 2380.0, 0.0, 0.0001, 0.0, 438.0, 0.0, 0.0, 1.0, -438.0, 438.0], + [2896.0, 2382.0, 2381.0, 0.01264, 0.03802, 0.00273, 114.0, 0.0, 0.0, 1.0, -114.0, 114.0]]) + + # Load data + self.loads = DataFrame( + ['id', 'bus_id', 'Pd', 'Qd', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [3.0, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [4.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [5.0, 5.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [6.0, 6.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [7.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [8.0, 8.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [9.0, 9.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [10.0, 10.0, 12.23, 9.0, 0.0, 0.0, 0.0, 12.23, 12.23], + [11.0, 11.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [12.0, 12.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [13.0, 13.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [14.0, 14.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [15.0, 15.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [16.0, 16.0, 54.88, 100.0, 0.0, 0.0, 0.0, 54.88, 54.88], + [17.0, 17.0, 77.0, 150.0, 0.0, 0.0, 0.0, 77.0, 77.0], + [18.0, 18.0, 153.0, 350.0, 0.0, 0.0, 0.0, 153.0, 153.0], + [19.0, 19.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [20.0, 20.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [21.0, 21.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [22.0, 22.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [23.0, 23.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [24.0, 24.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [25.0, 25.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [26.0, 26.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [27.0, 27.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [28.0, 28.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [29.0, 29.0, 25.98, 60.0, 0.0, 0.0, 0.0, 25.98, 25.98], + [30.0, 30.0, 25.98, 60.0, 0.0, 0.0, 0.0, 25.98, 25.98], + [31.0, 31.0, 20.98, 50.0, 0.0, 0.0, 0.0, 20.98, 20.98], + [32.0, 32.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [33.0, 33.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [34.0, 34.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [35.0, 35.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [36.0, 36.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [37.0, 37.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [38.0, 38.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [39.0, 39.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [40.0, 40.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [41.0, 41.0, 11.99, 30.0, 0.0, 0.0, 0.0, 11.99, 11.99], + [42.0, 42.0, 11.99, 30.0, 0.0, 0.0, 0.0, 11.99, 11.99], + [43.0, 43.0, 23.98, 60.0, 0.0, 0.0, 0.0, 23.98, 23.98], + [44.0, 44.0, 23.98, 60.0, 0.0, 0.0, 0.0, 23.98, 23.98], + [45.0, 45.0, 159.84, 75.0, 0.0, 0.0, 0.0, 159.84, 159.84], + [46.0, 46.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [47.0, 47.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [48.0, 48.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [49.0, 49.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [50.0, 50.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [51.0, 51.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [52.0, 52.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [53.0, 53.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [54.0, 54.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [55.0, 55.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [56.0, 56.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [57.0, 57.0, 22.98, 10.96, 0.0, 0.0, 0.0, 22.98, 22.98], + [58.0, 58.0, 21.98, 5.79, 0.0, 0.0, 0.0, 21.98, 21.98], + [59.0, 59.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [60.0, 60.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [61.0, 61.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [62.0, 62.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [63.0, 63.0, 37.37, 52.69, 0.0, 0.0, 0.0, 37.37, 37.37], + [64.0, 64.0, 35.37, 55.32, 0.0, 0.0, 0.0, 35.37, 35.37], + [65.0, 65.0, 13.39, 2.02, 0.0, 0.0, 0.0, 13.39, 13.39], + [66.0, 66.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [67.0, 67.0, 60.4, 92.1, 0.0, 0.0, 0.0, 60.4, 60.4], + [68.0, 68.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [69.0, 69.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [70.0, 70.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [71.0, 71.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [72.0, 72.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [73.0, 73.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [74.0, 74.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [75.0, 75.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [76.0, 76.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [77.0, 77.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [78.0, 78.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [79.0, 79.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [80.0, 80.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [81.0, 81.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [82.0, 82.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [83.0, 83.0, 15.99, 22.97, 0.0, 0.0, 0.0, 15.99, 15.99], + [84.0, 84.0, 15.79, 22.27, 0.0, 0.0, 0.0, 15.79, 15.79], + [85.0, 85.0, 9.99, 17.01, 0.0, 0.0, 0.0, 9.99, 9.99], + [86.0, 86.0, 9.99, 16.66, 0.0, 0.0, 0.0, 9.99, 9.99], + [87.0, 87.0, 11.09, 16.22, 0.0, 0.0, 0.0, 11.09, 11.09], + [88.0, 88.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [89.0, 89.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [90.0, 90.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [91.0, 91.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [92.0, 92.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [93.0, 93.0, 9.99, 16.39, 0.0, 0.0, 0.0, 9.99, 9.99], + [94.0, 94.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [95.0, 95.0, 6.89, 8.15, 0.0, 0.0, 0.0, 6.89, 6.89], + [96.0, 96.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [97.0, 97.0, 8.69, 5.26, 0.0, 0.0, 0.0, 8.69, 8.69], + [98.0, 98.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [99.0, 99.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [100.0, 100.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [101.0, 101.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [102.0, 102.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [103.0, 103.0, 18.09, 23.76, 0.0, 0.0, 0.0, 18.09, 18.09], + [104.0, 104.0, 33.68, 46.11, 0.0, 0.0, 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12.09, 12.09], + [2345.0, 2345.0, 17.49, 4.9, 0.0, 0.0, 0.0, 17.49, 17.49], + [2346.0, 2346.0, 9.99, 2.7, 0.0, 0.0, 0.0, 9.99, 9.99], + [2347.0, 2347.0, 18.19, 5.3, 0.0, 0.0, 0.0, 18.19, 18.19], + [2348.0, 2348.0, 12.49, 3.8, 0.0, 0.0, 0.0, 12.49, 12.49], + [2349.0, 2349.0, 8.29, 3.9, 0.0, 0.0, 0.0, 8.29, 8.29], + [2350.0, 2350.0, 11.99, 1.0, 0.0, 0.0, 0.0, 11.99, 11.99], + [2351.0, 2351.0, 8.79, 0.0, 0.0, 0.0, 0.0, 8.79, 8.79], + [2352.0, 2352.0, 18.49, 6.2, 0.0, 0.0, 0.0, 18.49, 18.49], + [2353.0, 2353.0, 21.98, 4.6, 0.0, 0.0, 0.0, 21.98, 21.98], + [2354.0, 2354.0, 19.59, 4.4, 0.0, 0.0, 0.0, 19.59, 19.59], + [2355.0, 2355.0, 8.99, 0.3, 0.0, 0.0, 0.0, 8.99, 8.99], + [2356.0, 2356.0, 19.19, 4.3, 0.0, 0.0, 0.0, 19.19, 19.19], + [2357.0, 2357.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2358.0, 2358.0, 4.1, 2.0, 0.0, 0.0, 0.0, 4.1, 4.1], + [2359.0, 2359.0, 12.49, 4.5, 0.0, 0.0, 0.0, 12.49, 12.49], + [2360.0, 2360.0, 22.78, 7.9, 0.0, 0.0, 0.0, 22.78, 22.78], + [2361.0, 2361.0, 18.59, 5.7, 0.0, 0.0, 0.0, 18.59, 18.59], + [2362.0, 2362.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2363.0, 2363.0, 23.38, 5.9, 0.0, 0.0, 0.0, 23.38, 23.38], + [2364.0, 2364.0, 6.5, 0.5, 0.0, 0.0, 0.0, 6.5, 6.5], + [2365.0, 2365.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2366.0, 2366.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2367.0, 2367.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2368.0, 2368.0, 32.98, 6.0, 0.0, 0.0, 0.0, 32.98, 32.98], + [2369.0, 2369.0, 2.0, 1.0, 0.0, 0.0, 0.0, 2.0, 2.0], + [2370.0, 2370.0, 11.49, 2.7, 0.0, 0.0, 0.0, 11.49, 11.49], + [2371.0, 2371.0, 12.99, 3.3, 0.0, 0.0, 0.0, 12.99, 12.99], + [2372.0, 2372.0, 49.95, 13.0, 0.0, 0.0, 0.0, 49.95, 49.95], + [2373.0, 2373.0, 39.97, 13.0, 0.0, 0.0, 0.0, 39.97, 39.97], + [2374.0, 2374.0, 9.59, 1.2, 0.0, 0.0, 0.0, 9.59, 9.59], + [2375.0, 2375.0, 10.99, 5.0, 0.0, 0.0, 0.0, 10.99, 10.99], + [2376.0, 2376.0, 21.98, 4.8, 0.0, 0.0, 0.0, 21.98, 21.98], + [2377.0, 2377.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2378.0, 2378.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2379.0, 2379.0, 12.99, 6.5, 0.0, 0.0, 0.0, 12.99, 12.99], + [2380.0, 2380.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2381.0, 2381.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2382.0, 2382.0, 3.0, 0.4, 0.0, 0.0, 0.0, 3.0, 3.0], + [2383.0, 2383.0, 50.0, 20.0, 0.0, 0.0, 0.0, 50.0, 50.0]]) + + self.real_params = True + super().__init__(*args, **kwargs) diff --git a/powergrid_case/transmission/Case29GB.py b/powergrid_case/transmission/Case29GB.py new file mode 100644 index 0000000000000000000000000000000000000000..b138fca6b9efc1bc0d7ba0c4b6c1bc764be6a882 --- /dev/null +++ b/powergrid_case/transmission/Case29GB.py @@ -0,0 +1,235 @@ +"""Power System Case: Case29GB (GB reduced network) + +Data Source: MATPOWER GBreducednetwork.m +Description: Reduced model of GB (Great Britain) network + 29 buses, 66 generators, 99 transmission lines + Data provided by Manolis Belivanis from Strathclyde + +Generator cost parameters are simulated using the same methodology as Case118. +""" +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case29GB(ClearCase): + GRID_TYPE = "transmission" + BUS_COUNT = 29 + VOLTAGE_LEVEL = "HV" + SOURCE = "custom" + DESCRIPTION = "GB reduced 29-bus transmission network" + + def __init__(self, *args, **kwargs): + self.nodes = DataFrame(['id'], range(1, 30)) + + self.units = DataFrame( + ['id', 'bus_id', 'type', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min', 'ramp_up', 'ramp_down', 'init_start_up_cost', 'keep_time', 'init_power', 'init_state', 'min_up_time', 'min_down_time', 'init_no_load_cost'], + [ + [1, 1, 'nuclear', 0.000194, -0.159251, 61.0, 668, 134, 0.7, 0.7, 22500, 96, 494, 1, 96, 96, 10323.78], + [2, 1, 'coal', 0.000815, -0.379332, 128.0, 554, 111, 0.7, 0.7, 9000, 96, 550, 1, 4, 4, 18334.91], + [3, 1, 'coal', 0.002778, -0.7005, 134.0, 300, 60, 0.7, 0.7, 9000, -96, 0, 0, 4, 4, 10468.65], + [4, 1, 'nuclear', 0.239723, -5.598947, 69.0, 19, 4, 0.7, 0.7, 22500, 96, 19, 1, 96, 96, 339.24], + [5, 2, 'nuclear', 0.033272, -2.085882, 68.0, 51, 10, 0.7, 0.7, 22500, 96, 36, 1, 96, 96, 895.29], + [6, 2, 'gas', 0.00017, -0.283228, 216.0, 1524, 305, 0.7, 0.7, 4500, 96, 1524, 1, 1, 1, 81431.65], + [7, 2, 'gas', 2.746597, -35.97, 282.0, 12, 2, 0.7, 0.7, 4500, 96, 12, 1, 1, 1, 878.79], + [8, 3, 'nuclear', 0.000285, -0.193067, 62.0, 551, 110, 0.7, 0.7, 22500, 96, 388, 1, 96, 96, 8680.87], + [9, 3, 'nuclear', 0.239723, -5.598947, 69.0, 19, 4, 0.7, 0.7, 22500, 96, 14, 1, 96, 96, 339.24], + [10, 3, 'coal', 0.000818, -0.380018, 128.0, 553, 111, 0.7, 0.7, 9000, 96, 553, 1, 4, 4, 18301.81], + [11, 3, 'nuclear', 0.384622, -7.092, 69.0, 15, 3, 0.7, 0.7, 22500, 96, 15, 1, 96, 96, 267.82], + [12, 4, 'nuclear', 0.070645, -3.039429, 68.0, 35, 7, 0.7, 0.7, 22500, 96, 25, 1, 96, 96, 614.42], + [13, 4, 'coal', 4.8e-05, -0.09201, 97.0, 2284, 457, 0.7, 0.7, 9000, 96, 2284, 1, 4, 4, 54348.92], + [14, 4, 'coal', 0.001291, -0.477614, 131.0, 440, 88, 0.7, 0.7, 9000, 96, 340, 1, 4, 4, 14958.02], + [15, 4, 'gas', 0.005896, -1.666564, 268.0, 259, 52, 0.7, 0.7, 4500, 96, 259, 1, 1, 1, 17879.51], + [16, 5, 'gas', 0.000343, -0.401899, 232.0, 1074, 215, 0.7, 0.7, 4500, 96, 1074, 1, 1, 1, 62542.07], + [17, 5, 'gas', 0.747656, -18.766957, 281.0, 23, 5, 0.7, 0.7, 4500, 96, 23, 1, 1, 1, 1677.46], + [18, 6, 'nuclear', 4.5e-05, -0.076477, 54.0, 1391, 278, 0.7, 0.7, 22500, 96, 1002, 1, 96, 96, 18576.47], + [19, 6, 'coal', 0.229568, -6.368182, 141.0, 33, 7, 0.7, 0.7, 9000, 96, 33, 1, 4, 4, 1220.85], + [20, 6, 'nuclear', 0.036043, -2.17102, 68.0, 49, 10, 0.7, 0.7, 22500, 96, 49, 1, 96, 96, 860.18], + [21, 7, 'nuclear', 0.000878, -0.33879, 65.0, 314, 63, 0.7, 0.7, 22500, 96, 227, 1, 96, 96, 5229.59], + [22, 7, 'gas', 0.000268, -0.355259, 227.0, 1215, 243, 0.7, 0.7, 4500, 96, 1216, 1, 1, 1, 68930.4], + [23, 7, 'coal', 0.000206, -0.190699, 116.0, 1102, 220, 0.7, 0.7, 9000, 96, 1104, 1, 4, 4, 32504.04], + [24, 10, 'gas', 0.000271, -0.357614, 227.0, 1207, 241, 0.7, 0.7, 4500, 96, 1208, 1, 1, 1, 68476.54], + [25, 10, 'gas', 0.000113, -0.230208, 205.0, 1875, 375, 0.7, 0.7, 4500, 96, 1875, 1, 1, 1, 93999.08], + [26, 10, 'coal', 0.001417, -0.500357, 131.0, 420, 84, 0.7, 0.7, 9000, 96, 420, 1, 4, 4, 14278.11], + [27, 11, 'nuclear', 0.002671, -0.591, 66.0, 180, 36, 0.7, 0.7, 22500, 96, 130, 1, 96, 96, 3051.86], + [28, 11, 'gas', 6.8e-05, -0.179401, 191.0, 2406, 481, 0.7, 0.7, 4500, 96, 2406, 1, 1, 1, 110514.41], + [29, 11, 'coal', 6.3e-05, -0.105762, 102.0, 1987, 397, 0.7, 0.7, 9000, 96, 1961, 1, 4, 4, 50262.16], + [30, 11, 'gas', 0.016462, -2.784774, 274.0, 155, 31, 0.7, 0.7, 4500, 96, 155, 1, 1, 1, 10979.09], + [31, 11, 'gas', 0.000366, -0.415438, 234.0, 1039, 208, 0.7, 0.7, 4500, 96, 1039, 1, 1, 1, 61127.32], + [32, 12, 'coal', 0.00026, -0.214439, 119.0, 980, 196, 0.7, 0.7, 9000, 96, 980, 1, 4, 4, 29787.59], + [33, 12, 'gas', 0.000111, -0.228987, 205.0, 1885, 377, 0.7, 0.7, 4500, 96, 1885, 1, 1, 1, 94500.4], + [34, 12, 'gas', 0.008968, -2.055429, 271.0, 210, 42, 0.7, 0.7, 4500, 96, 210, 1, 1, 1, 14685.9], + [35, 12, 'coal', 6.2e-05, -0.104865, 101.0, 2004, 401, 0.7, 0.7, 9000, 96, 1096, 1, 4, 4, 50090.98], + [36, 15, 'coal', 4e-06, -0.026832, 55.0, 7832, 1566, 0.7, 0.7, 9000, 96, 7800, 1, 4, 4, 87683.16], + [37, 16, 'coal', 1.6e-05, -0.052709, 79.0, 3987, 797, 0.7, 0.7, 9000, 96, 3972, 1, 4, 4, 73342.86], + [38, 16, 'gas', 8e-06, -0.061312, 117.0, 7040, 1408, 0.7, 0.7, 4500, 96, 7041, 1, 1, 1, 167079.19], + [39, 16, 'gas', 0.000267, -0.354384, 227.0, 1218, 244, 0.7, 0.7, 4500, 96, 1218, 1, 1, 1, 69100.6], + [40, 17, 'coal', 6.1e-05, -0.103983, 101.0, 2021, 404, 0.7, 0.7, 9000, 96, 2000, 1, 4, 4, 50515.91], + [41, 18, 'coal', 6.4e-05, -0.106029, 102.0, 1982, 396, 0.7, 0.7, 9000, 96, 1960, 1, 4, 4, 50135.68], + [42, 18, 'gas', 0.007608, -1.893158, 270.0, 228, 46, 0.7, 0.7, 4500, 96, 228, 1, 1, 1, 15876.29], + [43, 19, 'gas', 4.9e-05, -0.151719, 180.0, 2845, 569, 0.7, 0.7, 4500, 96, 2845, 1, 1, 1, 121290.43], + [44, 19, 'nuclear', 0.000522, -0.261376, 64.0, 407, 81, 0.7, 0.7, 22500, 96, 407, 1, 96, 96, 6656.39], + [45, 20, 'coal', 0.000174, -0.175125, 115.0, 1200, 240, 0.7, 0.7, 9000, 96, 1200, 1, 4, 4, 35034.6], + [46, 20, 'nuclear', 0.000668, -0.2955, 64.0, 360, 72, 0.7, 0.7, 22500, 96, 360, 1, 96, 96, 5887.71], + [47, 21, 'gas', 0.000894, -0.649083, 249.0, 665, 133, 0.7, 0.7, 4500, 96, 665, 1, 1, 1, 42116.34], + [48, 22, 'gas', 0.00246, -1.076409, 261.0, 401, 80, 0.7, 0.7, 4500, 96, 401, 1, 1, 1, 26840.07], + [49, 23, 'coal', 1.7e-05, -0.055288, 81.0, 3801, 760, 0.7, 0.7, 9000, 96, 3772, 1, 4, 4, 72201.9], + [50, 23, 'coal', 0.001897, -0.578926, 132.0, 363, 73, 0.7, 0.7, 9000, 96, 363, 1, 4, 4, 12449.27], + [51, 23, 'coal', 0.001132, -0.447128, 130.0, 470, 94, 0.7, 0.7, 9000, 96, 470, 1, 4, 4, 15836.88], + [52, 23, 'gas', 2e-05, -0.097414, 150.0, 4431, 886, 0.7, 0.7, 4500, 96, 3081, 1, 1, 1, 149027.11], + [53, 23, 'gas', 0.039551, -4.3164, 277.0, 100, 20, 0.7, 0.7, 4500, -96, 0, 0, 1, 1, 7173.28], + [54, 25, 'gas', 8.8e-05, -0.203316, 198.0, 2123, 425, 0.7, 0.7, 4500, 96, 2123, 1, 1, 1, 101973.72], + [55, 25, 'coal', 0.000161, -0.168795, 114.0, 1245, 249, 0.7, 0.7, 9000, -96, 0, 0, 4, 4, 35974.9], + [56, 26, 'coal', 6.5e-05, -0.106892, 102.0, 1966, 393, 0.7, 0.7, 9000, 96, 1940, 1, 4, 4, 49730.95], + [57, 26, 'coal', 0.000195, -0.185809, 116.0, 1131, 226, 0.7, 0.7, 9000, 96, 1104, 1, 4, 4, 33359.41], + [58, 26, 'gas', 3.9e-05, -0.136379, 173.0, 3165, 633, 0.7, 0.7, 4500, 96, 2465, 1, 1, 1, 128286.44], + [59, 26, 'coal', 0.000136, -0.155092, 112.0, 1355, 271, 0.7, 0.7, 9000, -96, 0, 0, 4, 4, 38340.4], + [60, 27, 'gas', 0.000338, -0.399297, 232.0, 1081, 216, 0.7, 0.7, 4500, 96, 1082, 1, 1, 1, 62949.7], + [61, 27, 'nuclear', 0.000962, -0.3546, 65.0, 300, 60, 0.7, 0.7, 22500, 96, 216, 1, 96, 96, 4996.43], + [62, 28, 'gas', 0.000227, -0.327, 223.0, 1320, 264, 0.7, 0.7, 4500, 96, 1320, 1, 1, 1, 73303.35], + [63, 28, 'gas', 0.009142, -2.075192, 271.0, 208, 42, 0.7, 0.7, 4500, 96, 208, 1, 1, 1, 14546.03], + [64, 29, 'gas', 0.000249, -0.3423, 225.0, 1261, 252, 0.7, 0.7, 4500, 96, 1261, 1, 1, 1, 70783.51], + [65, 29, 'gas', 0.000483, -0.47695, 239.0, 905, 181, 0.7, 0.7, 4500, 96, 905, 1, 1, 1, 54601.22], + [66, 29, 'gas', 0.020179, -3.083143, 275.0, 140, 28, 0.7, 0.7, 4500, -96, 0, 0, 1, 1, 9958.6]]) + + self.lines = DataFrame( + ['id', 'from', 'to', 'x', 's', 'floor', 'cap'], + [ + [1, 1, 2, 0.02, 50.0, -525.0, 525.0], + [2, 1, 3, 0.15, 6.66667, -132.0, 132.0], + [3, 1, 2, 0.02, 50.0, -525.0, 525.0], + [4, 1, 3, 0.15, 6.66667, -132.0, 132.0], + [5, 2, 4, 0.065, 15.38462, -760.0, 760.0], + [6, 2, 4, 0.065, 15.38462, -760.0, 760.0], + [7, 4, 7, 0.0135, 74.07407, -1090.0, 1090.0], + [8, 4, 6, 0.023, 43.47826, -1500.0, 1500.0], + [9, 4, 6, 0.023, 43.47826, -1120.0, 1120.0], + [10, 4, 5, 0.024, 41.66667, -1000.0, 1000.0], + [11, 4, 5, 0.024, 41.66667, -1000.0, 1000.0], + [12, 4, 7, 0.0135, 74.07407, -1090.0, 1090.0], + [13, 5, 6, 0.01051, 95.14748, -1390.0, 1390.0], + [14, 5, 6, 0.01613, 61.99628, -1390.0, 1390.0], + [15, 6, 9, 0.00852, 117.37089, -2100.0, 2100.0], + [16, 6, 9, 0.00852, 117.37089, -2100.0, 2100.0], + [17, 7, 8, 0.0001, 10000.0, -2180.0, 2180.0], + [18, 7, 8, 0.0001, 10000.0, -2500.0, 2500.0], + [19, 7, 6, 0.2, 5.0, -950.0, 950.0], + [20, 7, 6, 0.2, 5.0, -950.0, 950.0], + [21, 8, 10, 0.0175, 57.14286, -3070.0, 3070.0], + [22, 8, 10, 0.0175, 57.14286, -3070.0, 3070.0], + [23, 9, 11, 0.0163, 61.34969, -1390.0, 1390.0], + [24, 9, 11, 0.0163, 61.34969, -1390.0, 1390.0], + [25, 9, 10, 0.02453, 40.76641, -855.0, 855.0], + [26, 9, 10, 0.0343, 29.15452, -775.0, 775.0], + [27, 10, 15, 0.00835, 119.76048, -4840.0, 4840.0], + [28, 10, 15, 0.0063, 158.73016, -4020.0, 4020.0], + [29, 11, 15, 0.042, 23.80952, -2520.0, 2520.0], + [30, 11, 15, 0.042, 23.80952, -2520.0, 2520.0], + [31, 11, 13, 0.0052, 192.30769, -2170.0, 2170.0], + [32, 11, 13, 0.0052, 192.30769, -2210.0, 2210.0], + [33, 11, 12, 0.0085, 117.64706, -3320.0, 3320.0], + [34, 11, 12, 0.0085, 117.64706, -3320.0, 3320.0], + [35, 12, 13, 0.01078, 92.76438, -3100.0, 3100.0], + [36, 12, 18, 0.009, 111.11111, -2400.0, 2400.0], + [37, 12, 18, 0.009, 111.11111, -2400.0, 2400.0], + [38, 12, 13, 0.01078, 92.76438, -3100.0, 3100.0], + [39, 13, 18, 0.007, 142.85714, -2400.0, 2400.0], + [40, 13, 18, 0.007, 142.85714, -2400.0, 2400.0], + [41, 13, 15, 0.023, 43.47826, -1240.0, 1240.0], + [42, 13, 15, 0.023, 43.47826, -955.0, 955.0], + [43, 13, 14, 0.01163, 85.98452, -1040.0, 1040.0], + [44, 13, 14, 0.01201, 83.26395, -1040.0, 1040.0], + [45, 14, 16, 0.016, 62.5, -2580.0, 2580.0], + [46, 14, 16, 0.018, 55.55556, -625.0, 625.0], + [47, 15, 16, 0.0052, 192.30769, -2770.0, 2770.0], + [48, 15, 16, 0.00172, 581.39535, -5540.0, 5540.0], + [49, 15, 14, 0.00222, 450.45045, -5000.0, 5000.0], + [50, 15, 14, 0.00222, 450.45045, -5000.0, 5000.0], + [51, 16, 19, 0.0141, 70.92199, -2780.0, 2780.0], + [52, 16, 19, 0.0141, 70.92199, -3820.0, 3820.0], + [53, 17, 16, 0.01072, 93.28358, -2150.0, 2150.0], + [54, 17, 16, 0.01072, 93.28358, -1890.0, 1890.0], + [55, 17, 22, 0.0097, 103.09278, -2100.0, 2100.0], + [56, 17, 22, 0.0097, 103.09278, -2100.0, 2100.0], + [57, 18, 17, 0.0018, 555.55556, -3100.0, 3100.0], + [58, 18, 17, 0.0018, 555.55556, -3460.0, 3460.0], + [59, 18, 23, 0.0096, 104.16667, -1970.0, 1970.0], + [60, 18, 23, 0.0096, 104.16667, -1970.0, 1970.0], + [61, 20, 26, 0.0023, 434.78261, -2780.0, 2780.0], + [62, 20, 26, 0.0023, 434.78261, -2780.0, 2780.0], + [63, 20, 19, 0.0213, 46.94836, -1590.0, 1590.0], + [64, 20, 19, 0.0143, 69.93007, -1590.0, 1590.0], + [65, 21, 16, 0.01824, 54.82456, -2780.0, 2780.0], + [66, 21, 16, 0.01824, 54.82456, -2780.0, 2780.0], + [67, 21, 25, 0.01, 100.0, -2780.0, 2780.0], + [68, 21, 25, 0.01, 100.0, -2780.0, 2780.0], + [69, 21, 20, 0.0048, 208.33333, -2780.0, 2780.0], + [70, 21, 20, 0.0048, 208.33333, -2780.0, 2780.0], + [71, 21, 19, 0.0059, 169.49153, -3030.0, 3030.0], + [72, 21, 19, 0.0059, 169.49153, -2780.0, 2780.0], + [73, 22, 16, 0.0172, 58.13953, -2010.0, 2010.0], + [74, 22, 16, 0.0172, 58.13953, -2010.0, 2010.0], + [75, 22, 25, 0.0041, 243.90244, -3275.0, 3275.0], + [76, 22, 25, 0.0041, 243.90244, -3275.0, 3275.0], + [77, 22, 21, 0.00111, 900.9009, -2780.0, 2780.0], + [78, 22, 21, 0.0061, 163.93443, -2780.0, 2780.0], + [79, 23, 29, 0.0182, 54.94505, -2010.0, 2010.0], + [80, 23, 24, 0.0008, 1250.0, -2780.0, 2780.0], + [81, 23, 24, 0.0007, 1428.57143, -4400.0, 4400.0], + [82, 23, 22, 0.003, 333.33333, -2780.0, 2780.0], + [83, 23, 22, 0.003, 333.33333, -2770.0, 2770.0], + [84, 23, 29, 0.0182, 54.94505, -2010.0, 2010.0], + [85, 24, 28, 0.007, 142.85714, -2210.0, 2210.0], + [86, 24, 25, 0.0091, 109.89011, -1390.0, 1390.0], + [87, 24, 25, 0.0091, 109.89011, -1390.0, 1390.0], + [88, 24, 28, 0.007, 142.85714, -2210.0, 2210.0], + [89, 25, 26, 0.0057, 175.4386, -6960.0, 6960.0], + [90, 25, 26, 0.0057, 175.4386, -5540.0, 5540.0], + [91, 27, 26, 0.00503, 198.80716, -3100.0, 3100.0], + [92, 27, 26, 0.00503, 198.80716, -3100.0, 3100.0], + [93, 28, 27, 0.00711, 140.64698, -3070.0, 3070.0], + [94, 28, 27, 0.00711, 140.64698, -3070.0, 3070.0], + [95, 29, 28, 0.00796, 125.62814, -2780.0, 2780.0], + [96, 29, 28, 0.00796, 125.62814, -2780.0, 2780.0], + [97, 3, 4, 0.041, 24.39024, -648.0, 648.0], + [98, 3, 4, 0.041, 24.39024, -648.0, 648.0], + [99, 3, 2, 0.077, 12.98701, -652.0, 652.0]]) + + self.loads = DataFrame( + ['id', 'bus_id', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [ + [1, 1, 0.0, 0.0, 0.0, 0.008309, 0.008309], + [2, 2, 0.0, 0.0, 0.0, 0.009108, 0.009108], + [3, 3, 0.0, 0.0, 0.0, 0.009853, 0.009853], + [4, 4, 0.0, 0.0, 0.0, 0.023222, 0.023222], + [5, 5, 0.0, 0.0, 0.0, 0.008912, 0.008912], + [6, 6, 0.0, 0.0, 0.0, 0.020879, 0.020879], + [7, 7, 0.0, 0.0, 0.0, 0.013227, 0.013227], + [8, 8, 0.0, 0.0, 0.0, 0.002086, 0.002086], + [9, 9, 0.0, 0.0, 0.0, 0.002308, 0.002308], + [10, 10, 0.0, 0.0, 0.0, 0.045468, 0.045468], + [11, 11, 0.0, 0.0, 0.0, 0.059653, 0.059653], + [12, 12, 0.0, 0.0, 0.0, 0.021109, 0.021109], + [13, 13, 0.0, 0.0, 0.0, 0.044811, 0.044811], + [14, 14, 0.0, 0.0, 0.0, 0.032507, 0.032507], + [15, 15, 0.0, 0.0, 0.0, 0.046746, 0.046746], + [16, 16, 0.0, 0.0, 0.0, 0.02853, 0.02853], + [17, 17, 0.0, 0.0, 0.0, 0.019192, 0.019192], + [18, 18, 0.0, 0.0, 0.0, 0.095196, 0.095196], + [19, 19, 0.0, 0.0, 0.0, 0.035845, 0.035845], + [20, 20, 0.0, 0.0, 0.0, 0.01824, 0.01824], + [21, 21, 0.0, 0.0, 0.0, 0.012463, 0.012463], + [22, 22, 0.0, 0.0, 0.0, 0.032312, 0.032312], + [23, 23, 0.0, 0.0, 0.0, 0.084047, 0.084047], + [24, 24, 0.0, 0.0, 0.0, 0.025175, 0.025175], + [25, 25, 0.0, 0.0, 0.0, 0.172816, 0.172816], + [26, 26, 0.0, 0.0, 0.0, 0.025281, 0.025281], + [27, 27, 0.0, 0.0, 0.0, 0.008114, 0.008114], + [28, 28, 0.0, 0.0, 0.0, 0.048841, 0.048841], + [29, 29, 0.0, 0.0, 0.0, 0.045752, 0.045752]]) + + self.real_params = True + super().__init__(*args, **kwargs) + + +if __name__ == '__main__': + c = Case29GB() + c.check() diff --git a/powergrid_case/transmission/Case300.py b/powergrid_case/transmission/Case300.py new file mode 100644 index 0000000000000000000000000000000000000000..4d822b2b0179bec62f68bc4cfa2f119f32899173 --- /dev/null +++ b/powergrid_case/transmission/Case300.py @@ -0,0 +1,1160 @@ +"""Power System Case: 300 + +Data Source: MATPOWER case file +Base MVA: 100.0 MVA +Base kV: 115.0 kV + +All values are in standard MATPOWER units (MW, MVAr, p.u.) + + +Nodes (bus) columns: + id, type, Pd, Qd, Gs, Bs, Vm, Va, baseKV, Vmax, Vmin + - type: 1=PQ, 2=PV, 3=Slack + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - Gs/Bs: Shunt conductance/susceptance (MW/MVAr at V=1.0 p.u.) + - Vm: Voltage magnitude (p.u.) + - Va: Voltage angle (degrees) + - baseKV: Base voltage (kV) + - Vmax/Vmin: Voltage limits (p.u.) + +Units (generators) columns: + id, bus_id, Pg, Qg, Qmax, Qmin, Vg, mBase, status, Pmax, Pmin, mc_a, mc_b, mc_c + - Pg/Qg: Active/Reactive power output (MW/MVAr) + - Qmax/Qmin: Reactive power limits (MVAr) + - Vg: Voltage setpoint (p.u.) + - mBase: Machine base (MVA) + - status: >0 in-service, <=0 out-of-service + - Pmax/Pmin: Active power limits (MW) + - mc_a/mc_b/mc_c: Marginal cost coefficients (quadratic) + +Lines (branches) columns: + id, from, to, r, x, b, rateA, ratio, angle, status, floor, cap + - r/x: Resistance/Reactance (p.u.) + - b: Line charging susceptance (p.u.) + - rateA: Long-term rating (MVA) + - ratio: Transformer tap ratio (0 for line) + - angle: Transformer phase shift (degrees) + - status: 1=in-service, 0=out-of-service + - floor/cap: Power flow limits (MW) + +Loads columns: + id, bus_id, Pd, Qd, mc_a, mc_b, mc_c, d_max, d_min + - Pd/Qd: Active/Reactive power demand (MW/MVAr) + - mc_a/mc_b/mc_c: Marginal utility coefficients + - d_max/d_min: Demand limits (MW) +""" +from math import inf + +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case300(ClearCase): + GRID_TYPE = "transmission" + BUS_COUNT = 300 + VOLTAGE_LEVEL = "HV" + SOURCE = "MATPOWER" + DESCRIPTION = "IEEE 300-bus test system" + + def __init__(self, *args, **kwargs): + # System base values + self.baseMVA = 100.0 + self.baseKV = 115.0 + + # Node (bus) data + self.nodes = DataFrame( + ['id', 'type', 'Pd', 'Qd', 'Gs', 'Bs', 'Vm', 'Va', 'baseKV', 'Vmax', 'Vmin'], + [[1.0, 1.0, 90.0, 49.0, 0.0, 0.0, 1.0284, 5.95, 115.0, 1.06, 0.94], + [2.0, 1.0, 56.0, 15.0, 0.0, 0.0, 1.0354, 7.74, 115.0, 1.06, 0.94], + [3.0, 1.0, 20.0, 0.0, 0.0, 0.0, 0.9971, 6.64, 230.0, 1.06, 0.94], + [4.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0308, 4.71, 345.0, 1.06, 0.94], + [5.0, 1.0, 353.0, 130.0, 0.0, 0.0, 1.0191, 4.68, 115.0, 1.06, 0.94], + [6.0, 1.0, 120.0, 41.0, 0.0, 0.0, 1.0312, 6.99, 115.0, 1.06, 0.94], + [7.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.9934, 6.19, 230.0, 1.06, 0.94], + [8.0, 2.0, 63.0, 14.0, 0.0, 0.0, 1.0153, 2.4, 115.0, 1.06, 0.94], + [9.0, 1.0, 96.0, 43.0, 0.0, 0.0, 1.0034, 2.85, 115.0, 1.06, 0.94], + [10.0, 2.0, 153.0, 33.0, 0.0, 0.0, 1.0205, 1.35, 230.0, 1.06, 0.94], + [11.0, 1.0, 83.0, 21.0, 0.0, 0.0, 1.0057, 2.46, 115.0, 1.06, 0.94], + [12.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.9974, 5.21, 230.0, 1.06, 0.94], + [13.0, 1.0, 58.0, 10.0, 0.0, 0.0, 0.9977, -0.55, 115.0, 1.06, 0.94], + [14.0, 1.0, 160.0, 60.0, 0.0, 0.0, 0.9991, -4.81, 115.0, 1.06, 0.94], + [15.0, 1.0, 126.7, 23.0, 0.0, 0.0, 1.0343, -8.59, 115.0, 1.06, 0.94], + [16.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0315, -2.65, 345.0, 1.06, 0.94], + [17.0, 1.0, 561.0, 220.0, 0.0, 0.0, 1.0649, -13.1, 115.0, 1.06, 0.94], + [19.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.982, 1.08, 230.0, 1.06, 0.94], + [20.0, 2.0, 605.0, 120.0, 0.0, 0.0, 1.001, -2.46, 115.0, 1.06, 0.94], + [21.0, 1.0, 77.0, 1.0, 0.0, 0.0, 0.9752, 1.62, 230.0, 1.06, 0.94], + [22.0, 1.0, 81.0, 23.0, 0.0, 0.0, 0.9963, -1.97, 115.0, 1.06, 0.94], + [23.0, 1.0, 21.0, 7.0, 0.0, 0.0, 1.0501, 3.94, 115.0, 1.06, 0.94], + [24.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0057, 6.02, 230.0, 1.06, 0.94], + [25.0, 1.0, 45.0, 12.0, 0.0, 0.0, 1.0234, 1.44, 115.0, 1.06, 0.94], + [26.0, 1.0, 28.0, 9.0, 0.0, 0.0, 0.9986, -1.73, 115.0, 1.06, 0.94], + [27.0, 1.0, 69.0, 13.0, 0.0, 0.0, 0.975, -4.9, 115.0, 1.06, 0.94], + [33.0, 1.0, 55.0, 6.0, 0.0, 0.0, 1.0244, -12.02, 115.0, 1.06, 0.94], + [34.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0414, -7.94, 345.0, 1.06, 0.94], + [35.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.9757, -25.72, 115.0, 1.06, 0.94], + [36.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0011, -22.59, 230.0, 1.06, 0.94], + [37.0, 1.0, 85.0, 32.0, 0.0, 0.0, 1.0201, -11.23, 115.0, 1.06, 0.94], + [38.0, 1.0, 155.0, 18.0, 0.0, 0.0, 1.0202, -12.56, 115.0, 1.06, 0.94], + [39.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0535, -5.81, 345.0, 1.06, 0.94], + [40.0, 1.0, 46.0, -21.0, 0.0, 0.0, 1.0216, -12.78, 115.0, 1.06, 0.94], + [41.0, 1.0, 86.0, 0.0, 0.0, 0.0, 1.0292, -10.45, 115.0, 1.06, 0.94], + [42.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0448, -7.44, 345.0, 1.06, 0.94], + [43.0, 1.0, 39.0, 9.0, 0.0, 0.0, 1.0006, -16.79, 115.0, 1.06, 0.94], + [44.0, 1.0, 195.0, 29.0, 0.0, 0.0, 1.0086, -17.47, 115.0, 1.06, 0.94], + [45.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0215, -14.74, 230.0, 1.06, 0.94], + [46.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0344, -11.75, 345.0, 1.06, 0.94], + [47.0, 1.0, 58.0, 11.8, 0.0, 0.0, 0.9777, -23.17, 115.0, 1.06, 0.94], + [48.0, 1.0, 41.0, 19.0, 0.0, 0.0, 1.0019, -16.09, 115.0, 1.06, 0.94], + [49.0, 1.0, 92.0, 26.0, 0.0, 0.0, 1.0475, -2.95, 115.0, 1.06, 0.94], + [51.0, 1.0, -5.0, 5.0, 0.0, 0.0, 1.0253, -8.15, 115.0, 1.06, 0.94], + [52.0, 1.0, 61.0, 28.0, 0.0, 0.0, 0.9979, -11.86, 115.0, 1.06, 0.94], + [53.0, 1.0, 69.0, 3.0, 0.0, 0.0, 0.9959, -17.6, 115.0, 1.06, 0.94], + [54.0, 1.0, 10.0, 1.0, 0.0, 0.0, 1.005, -16.25, 115.0, 1.06, 0.94], + [55.0, 1.0, 22.0, 10.0, 0.0, 0.0, 1.015, -12.21, 115.0, 1.06, 0.94], + [57.0, 1.0, 98.0, 20.0, 0.0, 0.0, 1.0335, -8.0, 115.0, 1.06, 0.94], + [58.0, 1.0, 14.0, 1.0, 0.0, 0.0, 0.9918, -5.99, 115.0, 1.06, 0.94], + [59.0, 1.0, 218.0, 106.0, 0.0, 0.0, 0.9789, -5.29, 115.0, 1.06, 0.94], + [60.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0246, -9.56, 230.0, 1.06, 0.94], + [61.0, 1.0, 227.0, 110.0, 0.0, 0.0, 0.9906, -3.47, 115.0, 1.06, 0.94], + [62.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.016, -1.1, 230.0, 1.06, 0.94], + [63.0, 2.0, 70.0, 30.0, 0.0, 0.0, 0.9583, -17.62, 115.0, 1.06, 0.94], + [64.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.948, -12.97, 230.0, 1.06, 0.94], + [69.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.963, -25.66, 115.0, 1.06, 0.94], + [70.0, 1.0, 56.0, 20.0, 0.0, 0.0, 0.9513, -35.16, 115.0, 1.06, 0.94], + [71.0, 1.0, 116.0, 38.0, 0.0, 0.0, 0.9793, -29.88, 115.0, 1.06, 0.94], + [72.0, 1.0, 57.0, 19.0, 0.0, 0.0, 0.9696, -27.48, 115.0, 1.06, 0.94], + [73.0, 1.0, 224.0, 71.0, 0.0, 0.0, 0.9775, -25.77, 115.0, 1.06, 0.94], + [74.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.9964, -22.0, 230.0, 1.06, 0.94], + [76.0, 2.0, 208.0, 107.0, 0.0, 0.0, 0.9632, -26.54, 115.0, 1.06, 0.94], + [77.0, 1.0, 74.0, 28.0, 0.0, 0.0, 0.9837, -24.94, 115.0, 1.06, 0.94], + [78.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.99, -24.05, 115.0, 1.06, 0.94], + [79.0, 1.0, 48.0, 14.0, 0.0, 0.0, 0.982, -24.97, 115.0, 1.06, 0.94], + [80.0, 1.0, 28.0, 7.0, 0.0, 0.0, 0.9872, -24.97, 115.0, 1.06, 0.94], + [81.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.034, -18.89, 345.0, 1.06, 0.94], + [84.0, 2.0, 37.0, 13.0, 0.0, 0.0, 1.025, 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0.94], + [103.0, 1.0, 32.0, 0.0, 0.0, 0.0, 1.0288, -12.06, 115.0, 1.06, 0.94], + [104.0, 1.0, 8.6, 0.0, 0.0, 0.0, 0.9958, -17.33, 115.0, 1.06, 0.94], + [105.0, 1.0, 49.6, 0.0, 0.0, 0.0, 1.0223, -12.94, 115.0, 1.06, 0.94], + [107.0, 1.0, 4.6, 0.0, 0.0, 0.0, 1.0095, -16.03, 115.0, 1.06, 0.94], + [108.0, 2.0, 112.1, 0.0, 0.0, 0.0, 0.99, -20.26, 115.0, 1.06, 0.94], + [109.0, 1.0, 30.7, 0.0, 0.0, 0.0, 0.9749, -26.06, 115.0, 1.06, 0.94], + [110.0, 1.0, 63.0, 0.0, 0.0, 0.0, 0.973, -24.72, 115.0, 1.06, 0.94], + [112.0, 1.0, 19.6, 0.0, 0.0, 0.0, 0.9725, -28.69, 115.0, 1.06, 0.94], + [113.0, 1.0, 26.2, 0.0, 0.0, 0.0, 0.97, -25.38, 115.0, 1.06, 0.94], + [114.0, 1.0, 18.2, 0.0, 0.0, 0.0, 0.9747, -28.59, 115.0, 1.06, 0.94], + [115.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.9603, -13.57, 115.0, 1.06, 0.94], + [116.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0249, -12.69, 115.0, 1.06, 0.94], + [117.0, 1.0, 0.0, 0.0, 0.0, 325.0, 0.9348, -4.72, 115.0, 1.06, 0.94], + [118.0, 1.0, 14.1, 650.0, 0.0, 0.0, 0.9298, -4.12, 115.0, 1.06, 0.94], + [119.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0435, 5.17, 115.0, 1.06, 0.94], + [120.0, 1.0, 777.0, 215.0, 0.0, 55.0, 0.9584, -8.77, 115.0, 1.06, 0.94], + [121.0, 1.0, 535.0, 55.0, 0.0, 0.0, 0.9871, -12.64, 115.0, 1.06, 0.94], + [122.0, 1.0, 229.1, 11.8, 0.0, 0.0, 0.9728, -14.36, 115.0, 1.06, 0.94], + [123.0, 1.0, 78.0, 1.4, 0.0, 0.0, 1.0006, -17.64, 115.0, 1.06, 0.94], + [124.0, 2.0, 276.4, 59.3, 0.0, 0.0, 1.0233, -13.49, 115.0, 1.06, 0.94], + [125.0, 2.0, 514.8, 82.7, 0.0, 0.0, 1.0103, -18.43, 115.0, 1.06, 0.94], + [126.0, 1.0, 57.9, 5.1, 0.0, 0.0, 0.9978, -12.86, 115.0, 1.06, 0.94], + [127.0, 1.0, 380.8, 37.0, 0.0, 0.0, 1.0001, -10.52, 230.0, 1.06, 0.94], + [128.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0024, -4.78, 230.0, 1.06, 0.94], + [129.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0028, -4.4, 230.0, 1.06, 0.94], + [130.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0191, 5.56, 230.0, 1.06, 0.94], + [131.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.9861, 6.06, 230.0, 1.06, 0.94], + [132.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0045, 3.04, 230.0, 1.06, 0.94], + [133.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.002, -5.46, 230.0, 1.06, 0.94], + [134.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.022, -8.04, 230.0, 1.06, 0.94], + [135.0, 1.0, 169.2, 41.6, 0.0, 0.0, 1.0193, -6.76, 230.0, 1.06, 0.94], + [136.0, 1.0, 55.2, 18.2, 0.0, 0.0, 1.0476, 1.54, 230.0, 1.06, 0.94], + [137.0, 1.0, 273.6, 99.8, 0.0, 0.0, 1.0471, -1.45, 230.0, 1.06, 0.94], + [138.0, 2.0, 1019.2, 135.2, 0.0, 0.0, 1.055, -6.35, 230.0, 1.06, 0.94], + [139.0, 1.0, 595.0, 83.3, 0.0, 0.0, 1.0117, -3.57, 115.0, 1.06, 0.94], + [140.0, 1.0, 387.7, 114.7, 0.0, 0.0, 1.043, -3.44, 230.0, 1.06, 0.94], + [141.0, 2.0, 145.0, 58.0, 0.0, 0.0, 1.051, 0.05, 230.0, 1.06, 0.94], + [142.0, 1.0, 56.5, 24.5, 0.0, 0.0, 1.0155, -2.77, 230.0, 1.06, 0.94], + [143.0, 2.0, 89.5, 35.5, 0.0, 0.0, 1.0435, 4.03, 230.0, 1.06, 0.94], + [144.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.016, -0.7, 230.0, 1.06, 0.94], + [145.0, 1.0, 24.0, 14.0, 0.0, 0.0, 1.0081, -0.16, 230.0, 1.06, 0.94], + [146.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0528, 4.32, 230.0, 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0.0, 0.0, 0.9786, -17.25, 13.8, 1.06, 0.94], + [9053.0, 2.0, 26.48, 0.0, 0.0, 0.0, 1.0, -17.68, 13.8, 1.06, 0.94], + [9054.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, -6.83, 13.8, 1.06, 0.94], + [9055.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, -7.54, 13.8, 1.06, 0.94], + [9071.0, 1.0, 1.02, 0.35, 0.05, 0.0, 0.9752, -20.48, 0.6, 1.06, 0.94], + [9072.0, 1.0, 1.02, 0.35, 0.05, 0.0, 0.9803, -19.92, 0.6, 1.06, 0.94], + [9121.0, 1.0, 3.8, 1.25, 0.0, 0.0, 0.9799, -19.3, 6.6, 1.06, 0.94], + [9533.0, 1.0, 1.19, 0.41, 0.1, 0.0, 1.0402, -18.24, 2.3, 1.06, 0.94]]) + + # Generator (unit) data + self.units = DataFrame( + ['id', 'bus_id', 'Pg', 'Qg', 'Qmax', 'Qmin', 'Vg', 'mBase', 'status', 'Pmax', 'Pmin', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min'], + [[1.0, 8.0, 0.0, 0.0, 10.0, -10.0, 1.0153, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [2.0, 10.0, 0.0, 0.0, 20.0, -20.0, 1.0205, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [3.0, 20.0, 0.0, 0.0, 20.0, -20.0, 1.001, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [4.0, 63.0, 0.0, 0.0, 25.0, -25.0, 0.9583, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [5.0, 76.0, 0.0, 0.0, 35.0, 12.0, 0.9632, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [6.0, 84.0, 375.0, 0.0, 240.0, -240.0, 1.025, 100.0, 1.0, 475.0, 0.0, 0.0, 0.0533333334, 20.0, 475.0, 0.0], + [7.0, 91.0, 155.0, 0.0, 96.0, -11.0, 1.052, 100.0, 1.0, 255.0, 0.0, 0.0, 0.129032258, 20.0, 255.0, 0.0], + [8.0, 92.0, 290.0, 0.0, 153.0, -153.0, 1.052, 100.0, 1.0, 390.0, 0.0, 0.0, 0.0689655172, 20.0, 390.0, 0.0], + [9.0, 98.0, 68.0, 0.0, 56.0, -30.0, 1.0, 100.0, 1.0, 168.0, 0.0, 0.0, 0.294117648, 20.0, 168.0, 0.0], + [10.0, 108.0, 117.0, 0.0, 77.0, -24.0, 0.99, 100.0, 1.0, 217.0, 0.0, 0.0, 0.170940171, 20.0, 217.0, 0.0], + [11.0, 119.0, 1930.0, 0.0, 1500.0, -500.0, 1.0435, 100.0, 1.0, 2030.0, 0.0, 0.0, 0.0103626943, 20.0, 2030.0, 0.0], + [12.0, 124.0, 240.0, 0.0, 120.0, -60.0, 1.0233, 100.0, 1.0, 340.0, 0.0, 0.0, 0.0833333334, 20.0, 340.0, 0.0], + [13.0, 125.0, 0.0, 0.0, 200.0, -25.0, 1.0103, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [14.0, 138.0, 0.0, 0.0, 350.0, -125.0, 1.055, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [15.0, 141.0, 281.0, 0.0, 75.0, -50.0, 1.051, 100.0, 1.0, 381.0, 0.0, 0.0, 0.0711743772, 20.0, 381.0, 0.0], + [16.0, 143.0, 696.0, 0.0, 300.0, -100.0, 1.0435, 100.0, 1.0, 796.0, 0.0, 0.0, 0.0287356322, 20.0, 796.0, 0.0], + [17.0, 146.0, 84.0, 0.0, 35.0, -15.0, 1.0528, 100.0, 1.0, 184.0, 0.0, 0.0, 0.238095238, 20.0, 184.0, 0.0], + [18.0, 147.0, 217.0, 0.0, 100.0, -50.0, 1.0528, 100.0, 1.0, 317.0, 0.0, 0.0, 0.0921658986, 20.0, 317.0, 0.0], + [19.0, 149.0, 103.0, 0.0, 50.0, -25.0, 1.0735, 100.0, 1.0, 203.0, 0.0, 0.0, 0.1941747572, 20.0, 203.0, 0.0], + [20.0, 152.0, 372.0, 0.0, 175.0, -50.0, 1.0535, 100.0, 1.0, 472.0, 0.0, 0.0, 0.0537634408, 20.0, 472.0, 0.0], + [21.0, 153.0, 216.0, 0.0, 90.0, -50.0, 1.0435, 100.0, 1.0, 316.0, 0.0, 0.0, 0.0925925926, 20.0, 316.0, 0.0], + [22.0, 156.0, 0.0, 0.0, 15.0, -10.0, 0.963, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [23.0, 170.0, 205.0, 0.0, 90.0, -40.0, 0.929, 100.0, 1.0, 305.0, 0.0, 0.0, 0.0975609756, 20.0, 305.0, 0.0], + [24.0, 171.0, 0.0, 0.0, 150.0, -50.0, 0.9829, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [25.0, 176.0, 228.0, 0.0, 90.0, -45.0, 1.0522, 100.0, 1.0, 328.0, 0.0, 0.0, 0.0877192982, 20.0, 328.0, 0.0], + [26.0, 177.0, 84.0, 0.0, 35.0, -15.0, 1.0077, 100.0, 1.0, 184.0, 0.0, 0.0, 0.238095238, 20.0, 184.0, 0.0], + [27.0, 185.0, 200.0, 0.0, 80.0, -50.0, 1.0522, 100.0, 1.0, 300.0, 0.0, 0.0, 0.1, 20.0, 300.0, 0.0], + [28.0, 186.0, 1200.0, 0.0, 400.0, -100.0, 1.065, 100.0, 1.0, 1300.0, 0.0, 0.0, 0.01666666666, 20.0, 1300.0, 0.0], + [29.0, 187.0, 1200.0, 0.0, 400.0, -100.0, 1.065, 100.0, 1.0, 1300.0, 0.0, 0.0, 0.01666666666, 20.0, 1300.0, 0.0], + [30.0, 190.0, 475.0, 0.0, 300.0, -300.0, 1.0551, 100.0, 1.0, 575.0, 0.0, 0.0, 0.0421052632, 20.0, 575.0, 0.0], + [31.0, 191.0, 1973.0, 0.0, 1000.0, -1000.0, 1.0435, 100.0, 1.0, 2073.0, 0.0, 0.0, 0.01013684744, 20.0, 2073.0, 0.0], + [32.0, 198.0, 424.0, 0.0, 260.0, -260.0, 1.015, 100.0, 1.0, 524.0, 0.0, 0.0, 0.0471698114, 20.0, 524.0, 0.0], + [33.0, 213.0, 272.0, 0.0, 150.0, -150.0, 1.01, 100.0, 1.0, 372.0, 0.0, 0.0, 0.0735294118, 20.0, 372.0, 0.0], + [34.0, 220.0, 100.0, 0.0, 60.0, -60.0, 1.008, 100.0, 1.0, 200.0, 0.0, 0.0, 0.2, 20.0, 200.0, 0.0], + [35.0, 221.0, 450.0, 0.0, 320.0, -320.0, 1.0, 100.0, 1.0, 550.0, 0.0, 0.0, 0.0444444444, 20.0, 550.0, 0.0], + [36.0, 222.0, 250.0, 0.0, 300.0, -300.0, 1.05, 100.0, 1.0, 350.0, 0.0, 0.0, 0.08, 20.0, 350.0, 0.0], + [37.0, 227.0, 303.0, 0.0, 300.0, -300.0, 1.0, 100.0, 1.0, 403.0, 0.0, 0.0, 0.0660066006, 20.0, 403.0, 0.0], + [38.0, 230.0, 345.0, 0.0, 250.0, -250.0, 1.04, 100.0, 1.0, 445.0, 0.0, 0.0, 0.0579710144, 20.0, 445.0, 0.0], + [39.0, 233.0, 300.0, 0.0, 500.0, -500.0, 1.0, 100.0, 1.0, 400.0, 0.0, 0.0, 0.0666666666, 20.0, 400.0, 0.0], + [40.0, 236.0, 600.0, 0.0, 300.0, -300.0, 1.0165, 100.0, 1.0, 700.0, 0.0, 0.0, 0.0333333334, 20.0, 700.0, 0.0], + [41.0, 238.0, 250.0, 0.0, 200.0, -200.0, 1.01, 100.0, 1.0, 350.0, 0.0, 0.0, 0.08, 20.0, 350.0, 0.0], + [42.0, 239.0, 550.0, 0.0, 400.0, -400.0, 1.0, 100.0, 1.0, 650.0, 0.0, 0.0, 0.0363636364, 20.0, 650.0, 0.0], + [43.0, 241.0, 575.43, 0.0, 600.0, -600.0, 1.05, 100.0, 1.0, 675.43, 0.0, 0.0, 0.0347566168, 20.0, 675.43, 0.0], + [44.0, 242.0, 170.0, 0.0, 100.0, 40.0, 0.993, 100.0, 1.0, 270.0, 0.0, 0.0, 0.1176470588, 20.0, 270.0, 0.0], + [45.0, 243.0, 84.0, 0.0, 80.0, 40.0, 1.01, 100.0, 1.0, 184.0, 0.0, 0.0, 0.238095238, 20.0, 184.0, 0.0], + [46.0, 7001.0, 467.0, 0.0, 210.0, -210.0, 1.0507, 100.0, 1.0, 567.0, 0.0, 0.0, 0.0428265524, 20.0, 567.0, 0.0], + [47.0, 7002.0, 623.0, 0.0, 280.0, -280.0, 1.0507, 100.0, 1.0, 723.0, 0.0, 0.0, 0.0321027288, 20.0, 723.0, 0.0], + [48.0, 7003.0, 1210.0, 0.0, 420.0, -420.0, 1.0323, 100.0, 1.0, 1310.0, 0.0, 0.0, 0.01652892562, 20.0, 1310.0, 0.0], + [49.0, 7011.0, 234.0, 0.0, 100.0, -100.0, 1.0145, 100.0, 1.0, 334.0, 0.0, 0.0, 0.0854700854, 20.0, 334.0, 0.0], + [50.0, 7012.0, 372.0, 0.0, 224.0, -224.0, 1.0507, 100.0, 1.0, 472.0, 0.0, 0.0, 0.0537634408, 20.0, 472.0, 0.0], + [51.0, 7017.0, 330.0, 0.0, 350.0, 0.0, 1.0507, 100.0, 1.0, 430.0, 0.0, 0.0, 0.0606060606, 20.0, 430.0, 0.0], + [52.0, 7023.0, 185.0, 0.0, 120.0, 0.0, 1.0507, 100.0, 1.0, 285.0, 0.0, 0.0, 0.1081081082, 20.0, 285.0, 0.0], + [53.0, 7024.0, 410.0, 0.0, 224.0, -224.0, 1.029, 100.0, 1.0, 510.0, 0.0, 0.0, 0.0487804878, 20.0, 510.0, 0.0], + [54.0, 7039.0, 500.0, 0.0, 200.0, -200.0, 1.05, 100.0, 1.0, 600.0, 0.0, 0.0, 0.04, 20.0, 600.0, 0.0], + [55.0, 7044.0, 37.0, 0.0, 42.0, 0.0, 1.0145, 100.0, 1.0, 137.0, 0.0, 0.0, 0.54054054, 20.0, 137.0, 0.0], + [56.0, 7049.0, 0.0, 0.0, 10.0, 0.0, 1.0507, 100.0, 1.0, 2399.005, 0.0, 0.0, 0.02, 40.0, 2399.005, 0.0], + [57.0, 7055.0, 45.0, 0.0, 25.0, 0.0, 0.9967, 100.0, 1.0, 145.0, 0.0, 0.0, 0.444444444, 20.0, 145.0, 0.0], + [58.0, 7057.0, 165.0, 0.0, 90.0, -90.0, 1.0212, 100.0, 1.0, 265.0, 0.0, 0.0, 0.1212121212, 20.0, 265.0, 0.0], + [59.0, 7061.0, 400.0, 0.0, 150.0, -150.0, 1.0145, 100.0, 1.0, 500.0, 0.0, 0.0, 0.05, 20.0, 500.0, 0.0], + [60.0, 7062.0, 400.0, 0.0, 150.0, 0.0, 1.0017, 100.0, 1.0, 500.0, 0.0, 0.0, 0.05, 20.0, 500.0, 0.0], + [61.0, 7071.0, 116.0, 0.0, 87.0, 0.0, 0.9893, 100.0, 1.0, 216.0, 0.0, 0.0, 0.1724137932, 20.0, 216.0, 0.0], + [62.0, 7130.0, 1292.0, 0.0, 600.0, -100.0, 1.0507, 100.0, 1.0, 1392.0, 0.0, 0.0, 0.01547987616, 20.0, 1392.0, 0.0], + [63.0, 7139.0, 700.0, 0.0, 325.0, -125.0, 1.0507, 100.0, 1.0, 800.0, 0.0, 0.0, 0.0285714286, 20.0, 800.0, 0.0], + [64.0, 7166.0, 553.0, 0.0, 300.0, -200.0, 1.0145, 100.0, 1.0, 653.0, 0.0, 0.0, 0.0361663652, 20.0, 653.0, 0.0], + [65.0, 9002.0, 0.0, 0.0, 2.0, -2.0, 0.9945, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [66.0, 9051.0, 0.0, 0.0, 17.35, -17.35, 1.0, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [67.0, 9053.0, 0.0, 0.0, 12.83, -12.8, 1.0, 100.0, 1.0, 100.0, 0.0, 0.0, 0.02, 40.0, 100.0, 0.0], + [68.0, 9054.0, 50.0, 0.0, 38.0, -38.0, 1.0, 100.0, 1.0, 150.0, 0.0, 0.0, 0.4, 20.0, 150.0, 0.0], + [69.0, 9055.0, 8.0, 0.0, 6.0, -6.0, 1.0, 100.0, 1.0, 108.0, 0.0, 0.0, 2.5, 20.0, 108.0, 0.0]]) + + # Branch (line) data + self.lines = DataFrame( + ['id', 'from', 'to', 'r', 'x', 'b', 'rateA', 'ratio', 'angle', 'status', 'floor', 'cap'], + [[1.0, 37.0, 9001.0, 6e-05, 0.00046, 0.0, 0.0, 1.0082, 0.0, 1.0, 0.0, 0.0], + [2.0, 9001.0, 9005.0, 0.0008, 0.00348, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [3.0, 9001.0, 9006.0, 0.02439, 0.43682, 0.0, 0.0, 0.9668, 0.0, 1.0, 0.0, 0.0], + [4.0, 9001.0, 9012.0, 0.03624, 0.64898, 0.0, 0.0, 0.9796, 0.0, 1.0, 0.0, 0.0], + [5.0, 9005.0, 9051.0, 0.01578, 0.37486, 0.0, 0.0, 1.0435, 0.0, 1.0, 0.0, 0.0], + [6.0, 9005.0, 9052.0, 0.01578, 0.37486, 0.0, 0.0, 0.9391, 0.0, 1.0, 0.0, 0.0], + [7.0, 9005.0, 9053.0, 0.01602, 0.38046, 0.0, 0.0, 1.0435, 0.0, 1.0, 0.0, 0.0], + [8.0, 9005.0, 9054.0, 0.0, 0.152, 0.0, 0.0, 1.0435, 0.0, 1.0, 0.0, 0.0], + [9.0, 9005.0, 9055.0, 0.0, 0.8, 0.0, 0.0, 1.0435, 0.0, 1.0, 0.0, 0.0], + [10.0, 9006.0, 9007.0, 0.05558, 0.24666, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [11.0, 9006.0, 9003.0, 0.11118, 0.49332, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [12.0, 9006.0, 9003.0, 0.11118, 0.49332, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [13.0, 9012.0, 9002.0, 0.07622, 0.43286, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [14.0, 9012.0, 9002.0, 0.07622, 0.43286, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [15.0, 9002.0, 9021.0, 0.0537, 0.07026, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [16.0, 9021.0, 9023.0, 1.1068, 0.95278, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [17.0, 9021.0, 9022.0, 0.44364, 2.8152, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [18.0, 9002.0, 9024.0, 0.50748, 3.2202, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [19.0, 9023.0, 9025.0, 0.66688, 3.944, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [20.0, 9023.0, 9026.0, 0.6113, 3.6152, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [21.0, 9007.0, 9071.0, 0.4412, 2.9668, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [22.0, 9007.0, 9072.0, 0.30792, 2.057, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [23.0, 9007.0, 9003.0, 0.0558, 0.24666, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [24.0, 9003.0, 9031.0, 0.73633, 4.6724, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [25.0, 9003.0, 9032.0, 0.76978, 4.8846, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [26.0, 9003.0, 9033.0, 0.75732, 4.8056, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [27.0, 9003.0, 9044.0, 0.07378, 0.06352, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [28.0, 9044.0, 9004.0, 0.03832, 0.02894, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [29.0, 9004.0, 9041.0, 0.36614, 2.456, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [30.0, 9004.0, 9042.0, 1.0593, 5.4536, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [31.0, 9004.0, 9043.0, 0.1567, 1.6994, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [32.0, 9003.0, 9034.0, 0.13006, 1.3912, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [33.0, 9003.0, 9035.0, 0.54484, 3.4572, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [34.0, 9003.0, 9036.0, 0.15426, 1.6729, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [35.0, 9003.0, 9037.0, 0.3849, 2.5712, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [36.0, 9003.0, 9038.0, 0.4412, 2.9668, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [37.0, 9012.0, 9121.0, 0.23552, 0.99036, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [38.0, 9053.0, 9533.0, 0.0, 0.75, 0.0, 0.0, 0.9583, 0.0, 1.0, 0.0, 0.0], + [39.0, 1.0, 5.0, 0.001, 0.006, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [40.0, 2.0, 6.0, 0.001, 0.009, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [41.0, 2.0, 8.0, 0.006, 0.027, 0.054, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [42.0, 3.0, 7.0, 0.0, 0.003, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [43.0, 3.0, 19.0, 0.008, 0.069, 0.139, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [44.0, 3.0, 150.0, 0.001, 0.007, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [45.0, 4.0, 16.0, 0.002, 0.019, 1.127, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [46.0, 5.0, 9.0, 0.006, 0.029, 0.018, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [47.0, 7.0, 12.0, 0.001, 0.009, 0.07, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [48.0, 7.0, 131.0, 0.001, 0.007, 0.014, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [49.0, 8.0, 11.0, 0.013, 0.0595, 0.033, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [50.0, 8.0, 14.0, 0.013, 0.042, 0.081, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [51.0, 9.0, 11.0, 0.006, 0.027, 0.013, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [52.0, 11.0, 13.0, 0.008, 0.034, 0.018, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [53.0, 12.0, 21.0, 0.002, 0.015, 0.118, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [54.0, 13.0, 20.0, 0.006, 0.034, 0.016, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [55.0, 14.0, 15.0, 0.014, 0.042, 0.097, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [56.0, 15.0, 37.0, 0.065, 0.248, 0.121, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [57.0, 15.0, 89.0, 0.099, 0.248, 0.035, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [58.0, 15.0, 90.0, 0.096, 0.363, 0.048, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [59.0, 16.0, 42.0, 0.002, 0.022, 1.28, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [60.0, 19.0, 21.0, 0.002, 0.018, 0.036, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [61.0, 19.0, 87.0, 0.013, 0.08, 0.151, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [62.0, 20.0, 22.0, 0.016, 0.033, 0.015, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [63.0, 20.0, 27.0, 0.069, 0.186, 0.098, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [64.0, 21.0, 24.0, 0.004, 0.034, 0.28, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [65.0, 22.0, 23.0, 0.052, 0.111, 0.05, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [66.0, 23.0, 25.0, 0.019, 0.039, 0.018, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [67.0, 24.0, 319.0, 0.007, 0.068, 0.134, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [68.0, 25.0, 26.0, 0.036, 0.071, 0.034, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [69.0, 26.0, 27.0, 0.045, 0.12, 0.065, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [70.0, 26.0, 320.0, 0.043, 0.13, 0.014, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [71.0, 33.0, 34.0, 0.0, 0.063, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [72.0, 33.0, 38.0, 0.0025, 0.012, 0.013, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [73.0, 33.0, 40.0, 0.006, 0.029, 0.02, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [74.0, 33.0, 41.0, 0.007, 0.043, 0.026, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [75.0, 34.0, 42.0, 0.001, 0.008, 0.042, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [76.0, 35.0, 72.0, 0.012, 0.06, 0.008, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [77.0, 35.0, 76.0, 0.006, 0.014, 0.002, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [78.0, 35.0, 77.0, 0.01, 0.029, 0.003, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [79.0, 36.0, 88.0, 0.004, 0.027, 0.043, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [80.0, 37.0, 38.0, 0.008, 0.047, 0.008, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [81.0, 37.0, 40.0, 0.022, 0.064, 0.007, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [82.0, 37.0, 41.0, 0.01, 0.036, 0.02, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [83.0, 37.0, 49.0, 0.017, 0.081, 0.048, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [84.0, 37.0, 89.0, 0.102, 0.254, 0.033, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [85.0, 37.0, 90.0, 0.047, 0.127, 0.016, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [86.0, 38.0, 41.0, 0.008, 0.037, 0.02, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [87.0, 38.0, 43.0, 0.032, 0.087, 0.04, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [88.0, 39.0, 42.0, 0.0006, 0.0064, 0.404, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [89.0, 40.0, 48.0, 0.026, 0.154, 0.022, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [90.0, 41.0, 42.0, 0.0, 0.029, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [91.0, 41.0, 49.0, 0.065, 0.191, 0.02, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [92.0, 41.0, 51.0, 0.031, 0.089, 0.036, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [93.0, 42.0, 46.0, 0.002, 0.014, 0.806, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [94.0, 43.0, 44.0, 0.026, 0.072, 0.035, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [95.0, 43.0, 48.0, 0.095, 0.262, 0.032, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [96.0, 43.0, 53.0, 0.013, 0.039, 0.016, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [97.0, 44.0, 47.0, 0.027, 0.084, 0.039, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [98.0, 44.0, 54.0, 0.028, 0.084, 0.037, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [99.0, 45.0, 60.0, 0.007, 0.041, 0.312, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [100.0, 45.0, 74.0, 0.009, 0.054, 0.411, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [101.0, 46.0, 81.0, 0.005, 0.042, 0.69, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [102.0, 47.0, 73.0, 0.052, 0.145, 0.073, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [103.0, 47.0, 113.0, 0.043, 0.118, 0.013, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [104.0, 48.0, 107.0, 0.025, 0.062, 0.007, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [105.0, 49.0, 51.0, 0.031, 0.094, 0.043, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [106.0, 51.0, 52.0, 0.037, 0.109, 0.049, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [107.0, 52.0, 55.0, 0.027, 0.08, 0.036, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [108.0, 53.0, 54.0, 0.025, 0.073, 0.035, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [109.0, 54.0, 55.0, 0.035, 0.103, 0.047, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [110.0, 55.0, 57.0, 0.065, 0.169, 0.082, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [111.0, 57.0, 58.0, 0.046, 0.08, 0.036, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [112.0, 57.0, 63.0, 0.159, 0.537, 0.071, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [113.0, 58.0, 59.0, 0.009, 0.026, 0.005, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [114.0, 59.0, 61.0, 0.002, 0.013, 0.015, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [115.0, 60.0, 62.0, 0.009, 0.065, 0.485, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0], + [116.0, 62.0, 64.0, 0.016, 0.105, 0.203, 0.0, 0.0, 0.0, 1.0, 0.0, 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0.0], + [381.0, 202.0, 211.0, 0.0, 0.128, 0.0, 0.0, 1.01, 0.0, 1.0, 0.0, 0.0], + [382.0, 204.0, 2040.0, 0.02, 0.204, -0.012, 0.0, 1.05, 0.0, 1.0, 0.0, 0.0], + [383.0, 209.0, 198.0, 0.026, 0.211, 0.0, 0.0, 1.03, 0.0, 1.0, 0.0, 0.0], + [384.0, 211.0, 212.0, 0.003, 0.0122, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [385.0, 218.0, 219.0, 0.001, 0.0354, -0.01, 0.0, 0.97, 0.0, 1.0, 0.0, 0.0], + [386.0, 223.0, 224.0, 0.0012, 0.0195, -0.364, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [387.0, 229.0, 230.0, 0.001, 0.0332, 0.0, 0.0, 1.02, 0.0, 1.0, 0.0, 0.0], + [388.0, 234.0, 236.0, 0.0005, 0.016, 0.0, 0.0, 1.07, 0.0, 1.0, 0.0, 0.0], + [389.0, 238.0, 239.0, 0.0005, 0.016, 0.0, 0.0, 1.02, 0.0, 1.0, 0.0, 0.0], + [390.0, 196.0, 2040.0, 0.0001, 0.02, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + [391.0, 119.0, 1190.0, 0.001, 0.023, 0.0, 0.0, 1.0223, 0.0, 1.0, 0.0, 0.0], + [392.0, 120.0, 1200.0, 0.0, 0.023, 0.0, 0.0, 0.9284, 0.0, 1.0, 0.0, 0.0], + [393.0, 7002.0, 2.0, 0.001, 0.0146, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0], + 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0.0, 0.965, 0.0, 1.0, 0.0, 0.0], + [408.0, 7057.0, 57.0, 0.0, 0.05347, 0.0, 0.0, 0.95, 0.0, 1.0, 0.0, 0.0], + [409.0, 7044.0, 44.0, 0.0, 0.18181, 0.0, 0.0, 0.942, 0.0, 1.0, 0.0, 0.0], + [410.0, 7055.0, 55.0, 0.0, 0.19607, 0.0, 0.0, 0.942, 0.0, 1.0, 0.0, 0.0], + [411.0, 7071.0, 71.0, 0.0, 0.06896, 0.0, 0.0, 0.9565, 0.0, 1.0, 0.0, 0.0]]) + + # Load data + self.loads = DataFrame( + ['id', 'bus_id', 'Pd', 'Qd', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1.0, 1.0, 90.0, 49.0, 0.0, 0.0, 0.0, 90.0, 90.0], + [2.0, 2.0, 56.0, 15.0, 0.0, 0.0, 0.0, 56.0, 56.0], + [3.0, 3.0, 20.0, 0.0, 0.0, 0.0, 0.0, 20.0, 20.0], + [4.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [5.0, 5.0, 353.0, 130.0, 0.0, 0.0, 0.0, 353.0, 353.0], + [6.0, 6.0, 120.0, 41.0, 0.0, 0.0, 0.0, 120.0, 120.0], + [7.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [8.0, 8.0, 63.0, 14.0, 0.0, 0.0, 0.0, 63.0, 63.0], + [9.0, 9.0, 96.0, 43.0, 0.0, 0.0, 0.0, 96.0, 96.0], + [10.0, 10.0, 153.0, 33.0, 0.0, 0.0, 0.0, 153.0, 153.0], + [11.0, 11.0, 83.0, 21.0, 0.0, 0.0, 0.0, 83.0, 83.0], + [12.0, 12.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [13.0, 13.0, 58.0, 10.0, 0.0, 0.0, 0.0, 58.0, 58.0], + [14.0, 14.0, 160.0, 60.0, 0.0, 0.0, 0.0, 160.0, 160.0], + [15.0, 15.0, 126.7, 23.0, 0.0, 0.0, 0.0, 126.7, 126.7], + [16.0, 16.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [17.0, 17.0, 561.0, 220.0, 0.0, 0.0, 0.0, 561.0, 561.0], + [18.0, 19.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [19.0, 20.0, 605.0, 120.0, 0.0, 0.0, 0.0, 605.0, 605.0], + [20.0, 21.0, 77.0, 1.0, 0.0, 0.0, 0.0, 77.0, 77.0], + [21.0, 22.0, 81.0, 23.0, 0.0, 0.0, 0.0, 81.0, 81.0], + [22.0, 23.0, 21.0, 7.0, 0.0, 0.0, 0.0, 21.0, 21.0], + [23.0, 24.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [24.0, 25.0, 45.0, 12.0, 0.0, 0.0, 0.0, 45.0, 45.0], + [25.0, 26.0, 28.0, 9.0, 0.0, 0.0, 0.0, 28.0, 28.0], + [26.0, 27.0, 69.0, 13.0, 0.0, 0.0, 0.0, 69.0, 69.0], + [27.0, 33.0, 55.0, 6.0, 0.0, 0.0, 0.0, 55.0, 55.0], + [28.0, 34.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [29.0, 35.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [30.0, 36.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [31.0, 37.0, 85.0, 32.0, 0.0, 0.0, 0.0, 85.0, 85.0], + [32.0, 38.0, 155.0, 18.0, 0.0, 0.0, 0.0, 155.0, 155.0], + [33.0, 39.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [34.0, 40.0, 46.0, -21.0, 0.0, 0.0, 0.0, 46.0, 46.0], + [35.0, 41.0, 86.0, 0.0, 0.0, 0.0, 0.0, 86.0, 86.0], + [36.0, 42.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [37.0, 43.0, 39.0, 9.0, 0.0, 0.0, 0.0, 39.0, 39.0], + [38.0, 44.0, 195.0, 29.0, 0.0, 0.0, 0.0, 195.0, 195.0], + [39.0, 45.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [40.0, 46.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [41.0, 47.0, 58.0, 11.8, 0.0, 0.0, 0.0, 58.0, 58.0], + [42.0, 48.0, 41.0, 19.0, 0.0, 0.0, 0.0, 41.0, 41.0], + [43.0, 49.0, 92.0, 26.0, 0.0, 0.0, 0.0, 92.0, 92.0], + [44.0, 51.0, -5.0, 5.0, 0.0, 0.0, 0.0, -5.0, -5.0], + [45.0, 52.0, 61.0, 28.0, 0.0, 0.0, 0.0, 61.0, 61.0], + [46.0, 53.0, 69.0, 3.0, 0.0, 0.0, 0.0, 69.0, 69.0], + [47.0, 54.0, 10.0, 1.0, 0.0, 0.0, 0.0, 10.0, 10.0], + [48.0, 55.0, 22.0, 10.0, 0.0, 0.0, 0.0, 22.0, 22.0], + [49.0, 57.0, 98.0, 20.0, 0.0, 0.0, 0.0, 98.0, 98.0], + [50.0, 58.0, 14.0, 1.0, 0.0, 0.0, 0.0, 14.0, 14.0], + [51.0, 59.0, 218.0, 106.0, 0.0, 0.0, 0.0, 218.0, 218.0], + [52.0, 60.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [53.0, 61.0, 227.0, 110.0, 0.0, 0.0, 0.0, 227.0, 227.0], + [54.0, 62.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [55.0, 63.0, 70.0, 30.0, 0.0, 0.0, 0.0, 70.0, 70.0], + [56.0, 64.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [57.0, 69.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [58.0, 70.0, 56.0, 20.0, 0.0, 0.0, 0.0, 56.0, 56.0], + [59.0, 71.0, 116.0, 38.0, 0.0, 0.0, 0.0, 116.0, 116.0], + [60.0, 72.0, 57.0, 19.0, 0.0, 0.0, 0.0, 57.0, 57.0], + [61.0, 73.0, 224.0, 71.0, 0.0, 0.0, 0.0, 224.0, 224.0], + [62.0, 74.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [63.0, 76.0, 208.0, 107.0, 0.0, 0.0, 0.0, 208.0, 208.0], + [64.0, 77.0, 74.0, 28.0, 0.0, 0.0, 0.0, 74.0, 74.0], + [65.0, 78.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [66.0, 79.0, 48.0, 14.0, 0.0, 0.0, 0.0, 48.0, 48.0], + [67.0, 80.0, 28.0, 7.0, 0.0, 0.0, 0.0, 28.0, 28.0], + [68.0, 81.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [69.0, 84.0, 37.0, 13.0, 0.0, 0.0, 0.0, 37.0, 37.0], + [70.0, 85.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [71.0, 86.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [72.0, 87.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [73.0, 88.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [74.0, 89.0, 44.2, 0.0, 0.0, 0.0, 0.0, 44.2, 44.2], + [75.0, 90.0, 66.0, 0.0, 0.0, 0.0, 0.0, 66.0, 66.0], + [76.0, 91.0, 17.4, 0.0, 0.0, 0.0, 0.0, 17.4, 17.4], + [77.0, 92.0, 15.8, 0.0, 0.0, 0.0, 0.0, 15.8, 15.8], + [78.0, 94.0, 60.3, 0.0, 0.0, 0.0, 0.0, 60.3, 60.3], + [79.0, 97.0, 39.9, 0.0, 0.0, 0.0, 0.0, 39.9, 39.9], + [80.0, 98.0, 66.7, 0.0, 0.0, 0.0, 0.0, 66.7, 66.7], + [81.0, 99.0, 83.5, 0.0, 0.0, 0.0, 0.0, 83.5, 83.5], + [82.0, 100.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [83.0, 102.0, 77.8, 0.0, 0.0, 0.0, 0.0, 77.8, 77.8], + [84.0, 103.0, 32.0, 0.0, 0.0, 0.0, 0.0, 32.0, 32.0], + [85.0, 104.0, 8.6, 0.0, 0.0, 0.0, 0.0, 8.6, 8.6], + [86.0, 105.0, 49.6, 0.0, 0.0, 0.0, 0.0, 49.6, 49.6], + [87.0, 107.0, 4.6, 0.0, 0.0, 0.0, 0.0, 4.6, 4.6], + [88.0, 108.0, 112.1, 0.0, 0.0, 0.0, 0.0, 112.1, 112.1], + [89.0, 109.0, 30.7, 0.0, 0.0, 0.0, 0.0, 30.7, 30.7], + [90.0, 110.0, 63.0, 0.0, 0.0, 0.0, 0.0, 63.0, 63.0], + [91.0, 112.0, 19.6, 0.0, 0.0, 0.0, 0.0, 19.6, 19.6], + [92.0, 113.0, 26.2, 0.0, 0.0, 0.0, 0.0, 26.2, 26.2], + [93.0, 114.0, 18.2, 0.0, 0.0, 0.0, 0.0, 18.2, 18.2], + [94.0, 115.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [95.0, 116.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [96.0, 117.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [97.0, 118.0, 14.1, 650.0, 0.0, 0.0, 0.0, 14.1, 14.1], + [98.0, 119.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [99.0, 120.0, 777.0, 215.0, 0.0, 0.0, 0.0, 777.0, 777.0], + [100.0, 121.0, 535.0, 55.0, 0.0, 0.0, 0.0, 535.0, 535.0], + [101.0, 122.0, 229.1, 11.8, 0.0, 0.0, 0.0, 229.1, 229.1], + [102.0, 123.0, 78.0, 1.4, 0.0, 0.0, 0.0, 78.0, 78.0], + [103.0, 124.0, 276.4, 59.3, 0.0, 0.0, 0.0, 276.4, 276.4], + [104.0, 125.0, 514.8, 82.7, 0.0, 0.0, 0.0, 514.8, 514.8], + [105.0, 126.0, 57.9, 5.1, 0.0, 0.0, 0.0, 57.9, 57.9], + [106.0, 127.0, 380.8, 37.0, 0.0, 0.0, 0.0, 380.8, 380.8], + [107.0, 128.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [108.0, 129.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [109.0, 130.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [110.0, 131.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [111.0, 132.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [112.0, 133.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [113.0, 134.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [114.0, 135.0, 169.2, 41.6, 0.0, 0.0, 0.0, 169.2, 169.2], + [115.0, 136.0, 55.2, 18.2, 0.0, 0.0, 0.0, 55.2, 55.2], + [116.0, 137.0, 273.6, 99.8, 0.0, 0.0, 0.0, 273.6, 273.6], + [117.0, 138.0, 1019.2, 135.2, 0.0, 0.0, 0.0, 1019.2, 1019.2], + [118.0, 139.0, 595.0, 83.3, 0.0, 0.0, 0.0, 595.0, 595.0], + [119.0, 140.0, 387.7, 114.7, 0.0, 0.0, 0.0, 387.7, 387.7], + [120.0, 141.0, 145.0, 58.0, 0.0, 0.0, 0.0, 145.0, 145.0], + [121.0, 142.0, 56.5, 24.5, 0.0, 0.0, 0.0, 56.5, 56.5], + [122.0, 143.0, 89.5, 35.5, 0.0, 0.0, 0.0, 89.5, 89.5], + [123.0, 144.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [124.0, 145.0, 24.0, 14.0, 0.0, 0.0, 0.0, 24.0, 24.0], + [125.0, 146.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [126.0, 147.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [127.0, 148.0, 63.0, 25.0, 0.0, 0.0, 0.0, 63.0, 63.0], + [128.0, 149.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [129.0, 150.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [130.0, 151.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [131.0, 152.0, 17.0, 9.0, 0.0, 0.0, 0.0, 17.0, 17.0], + [132.0, 153.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [133.0, 154.0, 70.0, 5.0, 0.0, 0.0, 0.0, 70.0, 70.0], + [134.0, 155.0, 200.0, 50.0, 0.0, 0.0, 0.0, 200.0, 200.0], + [135.0, 156.0, 75.0, 50.0, 0.0, 0.0, 0.0, 75.0, 75.0], + [136.0, 157.0, 123.5, -24.3, 0.0, 0.0, 0.0, 123.5, 123.5], + [137.0, 158.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [138.0, 159.0, 33.0, 16.5, 0.0, 0.0, 0.0, 33.0, 33.0], + [139.0, 160.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [140.0, 161.0, 35.0, 15.0, 0.0, 0.0, 0.0, 35.0, 35.0], + [141.0, 162.0, 85.0, 24.0, 0.0, 0.0, 0.0, 85.0, 85.0], + [142.0, 163.0, 0.0, 0.4, 0.0, 0.0, 0.0, 0.0, 0.0], + [143.0, 164.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [144.0, 165.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [145.0, 166.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [146.0, 167.0, 299.9, 95.7, 0.0, 0.0, 0.0, 299.9, 299.9], + [147.0, 168.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [148.0, 169.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [149.0, 170.0, 481.8, 205.0, 0.0, 0.0, 0.0, 481.8, 481.8], + [150.0, 171.0, 763.6, 291.1, 0.0, 0.0, 0.0, 763.6, 763.6], + [151.0, 172.0, 26.5, 0.0, 0.0, 0.0, 0.0, 26.5, 26.5], + [152.0, 173.0, 163.5, 43.0, 0.0, 0.0, 0.0, 163.5, 163.5], + [153.0, 174.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [154.0, 175.0, 176.0, 83.0, 0.0, 0.0, 0.0, 176.0, 176.0], + [155.0, 176.0, 5.0, 4.0, 0.0, 0.0, 0.0, 5.0, 5.0], + [156.0, 177.0, 28.0, 12.0, 0.0, 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61.0, 61.0], + [227.0, 248.0, 29.0, 14.0, 0.0, 0.0, 0.0, 29.0, 29.0], + [228.0, 249.0, 29.0, 14.0, 0.0, 0.0, 0.0, 29.0, 29.0], + [229.0, 250.0, -23.0, -17.0, 0.0, 0.0, 0.0, -23.0, -23.0], + [230.0, 281.0, -33.1, -29.4, 0.0, 0.0, 0.0, -33.1, -33.1], + [231.0, 319.0, 115.8, -24.0, 0.0, 0.0, 0.0, 115.8, 115.8], + [232.0, 320.0, 2.4, -12.6, 0.0, 0.0, 0.0, 2.4, 2.4], + [233.0, 322.0, 2.4, -3.9, 0.0, 0.0, 0.0, 2.4, 2.4], + [234.0, 323.0, -14.9, 26.5, 0.0, 0.0, 0.0, -14.9, -14.9], + [235.0, 324.0, 24.7, -1.2, 0.0, 0.0, 0.0, 24.7, 24.7], + [236.0, 526.0, 145.3, -34.9, 0.0, 0.0, 0.0, 145.3, 145.3], + [237.0, 528.0, 28.1, -20.5, 0.0, 0.0, 0.0, 28.1, 28.1], + [238.0, 531.0, 14.0, 2.5, 0.0, 0.0, 0.0, 14.0, 14.0], + [239.0, 552.0, -11.1, -1.4, 0.0, 0.0, 0.0, -11.1, -11.1], + [240.0, 562.0, 50.5, 17.4, 0.0, 0.0, 0.0, 50.5, 50.5], + [241.0, 609.0, 29.6, 0.6, 0.0, 0.0, 0.0, 29.6, 29.6], + [242.0, 664.0, -113.7, 76.7, 0.0, 0.0, 0.0, -113.7, -113.7], + [243.0, 1190.0, 100.31, 29.17, 0.0, 0.0, 0.0, 100.31, 100.31], + [244.0, 1200.0, -100.0, 34.17, 0.0, 0.0, 0.0, -100.0, -100.0], + [245.0, 1201.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [246.0, 2040.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [247.0, 7001.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [248.0, 7002.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [249.0, 7003.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [250.0, 7011.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [251.0, 7012.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [252.0, 7017.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [253.0, 7023.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [254.0, 7024.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [255.0, 7039.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [256.0, 7044.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [257.0, 7049.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [258.0, 7055.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [259.0, 7057.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [260.0, 7061.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [261.0, 7062.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [262.0, 7071.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [263.0, 7130.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [264.0, 7139.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [265.0, 7166.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [266.0, 9001.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [267.0, 9002.0, 4.2, 0.0, 0.0, 0.0, 0.0, 4.2, 4.2], + [268.0, 9003.0, 2.71, 0.94, 0.0, 0.0, 0.0, 2.71, 2.71], + [269.0, 9004.0, 0.86, 0.28, 0.0, 0.0, 0.0, 0.86, 0.86], + [270.0, 9005.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [271.0, 9006.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [272.0, 9007.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [273.0, 9012.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [274.0, 9021.0, 4.75, 1.56, 0.0, 0.0, 0.0, 4.75, 4.75], + [275.0, 9022.0, 1.53, 0.53, 0.0, 0.0, 0.0, 1.53, 1.53], + [276.0, 9023.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [277.0, 9024.0, 1.35, 0.47, 0.0, 0.0, 0.0, 1.35, 1.35], + [278.0, 9025.0, 0.45, 0.16, 0.0, 0.0, 0.0, 0.45, 0.45], + [279.0, 9026.0, 0.45, 0.16, 0.0, 0.0, 0.0, 0.45, 0.45], + [280.0, 9031.0, 1.84, 0.64, 0.0, 0.0, 0.0, 1.84, 1.84], + [281.0, 9032.0, 1.39, 0.48, 0.0, 0.0, 0.0, 1.39, 1.39], + [282.0, 9033.0, 1.89, 0.65, 0.0, 0.0, 0.0, 1.89, 1.89], + [283.0, 9034.0, 1.55, 0.54, 0.0, 0.0, 0.0, 1.55, 1.55], + [284.0, 9035.0, 1.66, 0.58, 0.0, 0.0, 0.0, 1.66, 1.66], + [285.0, 9036.0, 3.03, 1.0, 0.0, 0.0, 0.0, 3.03, 3.03], + [286.0, 9037.0, 1.86, 0.64, 0.0, 0.0, 0.0, 1.86, 1.86], + [287.0, 9038.0, 2.58, 0.89, 0.0, 0.0, 0.0, 2.58, 2.58], + [288.0, 9041.0, 1.01, 0.35, 0.0, 0.0, 0.0, 1.01, 1.01], + [289.0, 9042.0, 0.81, 0.28, 0.0, 0.0, 0.0, 0.81, 0.81], + [290.0, 9043.0, 1.6, 0.52, 0.0, 0.0, 0.0, 1.6, 1.6], + [291.0, 9044.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [292.0, 9051.0, 35.81, 0.0, 0.0, 0.0, 0.0, 35.81, 35.81], + [293.0, 9052.0, 30.0, 23.0, 0.0, 0.0, 0.0, 30.0, 30.0], + [294.0, 9053.0, 26.48, 0.0, 0.0, 0.0, 0.0, 26.48, 26.48], + [295.0, 9054.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [296.0, 9055.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [297.0, 9071.0, 1.02, 0.35, 0.0, 0.0, 0.0, 1.02, 1.02], + [298.0, 9072.0, 1.02, 0.35, 0.0, 0.0, 0.0, 1.02, 1.02], + [299.0, 9121.0, 3.8, 1.25, 0.0, 0.0, 0.0, 3.8, 3.8], + [300.0, 9533.0, 1.19, 0.41, 0.0, 0.0, 0.0, 1.19, 1.19]]) + + self.real_params = True + super().__init__(*args, **kwargs) diff --git a/powergrid_case/transmission/Case5.py b/powergrid_case/transmission/Case5.py new file mode 100644 index 0000000000000000000000000000000000000000..7b3696ee3f3aaff7ae8d8dfab6723ae97e0a9b8b --- /dev/null +++ b/powergrid_case/transmission/Case5.py @@ -0,0 +1,53 @@ +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case5(ClearCase): + GRID_TYPE = "transmission" + BUS_COUNT = 5 + VOLTAGE_LEVEL = "HV" + SOURCE = "MATPOWER" + DESCRIPTION = "IEEE 5-bus test system" + + def __init__(self, *args, **kwargs): + # type: 1=PQ (load), 2=PV (gen), 3=Ref (θ=0 in DCOPF) + # Pd/Qd: nominal load at each bus (MW / MVAr) + self.nodes = DataFrame( + ['id', 'type', 'Pd', 'Qd', 'x', 'y'], + [[1.0, 3, 0.0, 0.0, 0, 0], # Reference bus (2 gens) + [2.0, 1, 300.0, 98.6, 3, 0], # Load bus + [3.0, 2, 300.0, 98.6, 4.5, 1], # Gen bus + [4.0, 2, 400.0, 131.5, 2, 2], # Gen bus + [5.0, 2, 0.0, 0.0, 0, 2]]) # Gen bus + + self.units = DataFrame( + ['id', 'bus_id', 'mc_a', 'mc_b', 'mc_c', 'p_max', 'p_min'], + [[1.0, 1.0, 0.0, 0.0, 14.0, 40.0, 5.0], + [2.0, 1.0, 0.0, 0.0, 15.0, 170.0, 10.0], + [3.0, 3.0, 0.0, 0.0, 30.0, 520.0, 20.0], + [4.0, 4.0, 0.0, 0.0, 40.0, 200.0, 10.0], + [5.0, 5.0, 0.0, 0.0, 10.0, 600.0, 20.0]]) + + self.lines = DataFrame( + ['id', 'from', 'to', 'x', 'floor', 'cap'], + [[1.0, 1.0, 2.0, 0.0281, -400.0, 400.0], + [2.0, 1.0, 4.0, 0.0304, 0.0, 0.0], + [3.0, 1.0, 5.0, 0.0064, 0.0, 0.0], + [4.0, 2.0, 3.0, 0.0108, 0.0, 0.0], + [5.0, 3.0, 4.0, 0.0297, 0.0, 0.0], + [6.0, 4.0, 5.0, 0.0297, -240.0, 240.0]]) + + self.loads = DataFrame( + ['id', 'bus_id', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [2.0, 2.0, 0.0, 0.0, 0.0, 500.0, 0.0], + [3.0, 3.0, 0.0, 0.0, 0.0, 600.0, 0.0], + [4.0, 4.0, 0.0, 0.0, 0.0, 400.0, 0.0], + [5.0, 5.0, 0.0, 0.0, 0.0, 0.0, 0.0]]) + + self.real_params = True + super().__init__(*args, **kwargs) + +if __name__ == '__main__': + c = Case5() + c.check() + print(c.get_node_ptdf()) diff --git a/powergrid_case/transmission/Case552GB.py b/powergrid_case/transmission/Case552GB.py new file mode 100644 index 0000000000000000000000000000000000000000..7436f397b287103aaecde54e9868c569f49d0fcb --- /dev/null +++ b/powergrid_case/transmission/Case552GB.py @@ -0,0 +1,39 @@ +"""Great Britain transmission case (:class:`Case552GB`). + +Built from the tabular dataset under ``powerzoo/case/source_mfile/``; regenerate +with ``build_case_from_csv.py`` when upstream inputs change. + +Not the same network as :class:`Case29GB` (29-bus MATPOWER reduced model). +Embedded tables: 552 buses, 2385 generators, 673 branches, 552 loads. +Nodes carry WGS84-like ``x``/``y``; units include a string ``type`` label. +""" + +from powerzoo.case.CaseBase import ClearCase, DataFrame + + +class Case552GB(ClearCase): + GRID_TYPE = "transmission" + BUS_COUNT = 552 + VOLTAGE_LEVEL = "HV" + SOURCE = "GB" + DESCRIPTION = "Great Britain 552-bus transmission (distinct from 29-bus Case29GB)" + + def __init__(self, *args, **kwargs): + self.nodes = DataFrame( + ['id', 'x', 'y'], + [[1.0, -2.8957458, 58.2568149], [2.0, -3.719714103, 56.08813281], [3.0, -3.1796917, 55.9246204], [4.0, -3.1786274, 55.9031338], [5.0, -2.93891761, 55.88469412], [6.0, -4.5707774, 55.8344676], [7.0, -4.1161377, 55.79148895], [8.0, -1.803404057, 55.0152563], [9.0, -1.409093389, 54.75666396], [10.0, -2.91670123, 54.02987179], [11.0, -3.6660007, 54.015637], [12.0, -2.8805172, 58.2499453], [13.0, -2.755971765, 54.01281882], [14.0, 1.6306869, 53.9394081], [15.0, -2.933961224, 53.87556701], [16.0, -1.2972567, 53.8695026], [17.0, 1.6376833, 53.766543], [18.0, -1.8053122, 53.7437311], [19.0, -1.831285551, 53.72329819], [20.0, -2.4534812, 53.7101582], [21.0, -1.804010541, 53.67674115], [22.0, -2.0685211, 53.6559798], [23.0, -2.9011666, 58.2463135], [24.0, -0.7254893, 53.6436974], [25.0, -1.0692832, 53.6366337], [26.0, -0.2943457, 53.6272955], [27.0, -1.284845914, 53.61097403], [28.0, -1.2528935, 53.6096987], [29.0, -0.232903, 53.5904792], [30.0, -1.6134812, 53.4963483], [31.0, -1.2467417, 53.444646], [32.0, 0.8000813, 53.4340319], [33.0, -0.817995162, 53.41570495], [34.0, -2.7128938, 58.096774], [35.0, -2.1051057, 53.4041771], [36.0, -1.4685122, 53.3912009], [37.0, -1.4472631, 53.3369511], [38.0, -2.7440555, 53.319391], [39.0, -2.819172467, 53.27963175], [40.0, 0.7855224, 53.2222743], [41.0, -4.1704357, 53.1498169], [42.0, -4.1561515, 53.1406872], [43.0, -4.0977029, 53.1225945], [44.0, -2.9917152, 58.0575386], [45.0, -3.1479469, 53.1167498], [46.0, -1.4045595, 52.8381758], [47.0, -0.0719683, 52.8381432], [48.0, -1.514203018, 52.82650701], [49.0, -1.8397943, 52.7277722], [50.0, -2.1094118, 52.6667274], [51.0, -1.7507603, 52.61627489], [52.0, -2.2407988, 52.61180729], [53.0, -1.7162298, 52.39505819], [54.0, -2.1834417, 52.39136439], [55.0, -2.7300015, 57.6863438], [56.0, -2.1426196, 52.36271319], [57.0, -2.1249941, 52.33712359], [58.0, 2.5060803, 52.24850499], [59.0, 0.7255421, 52.00039309], [60.0, 1.4246125, 51.99963089], [61.0, -2.5976167, 51.57876009], [62.0, -3.143064416, 51.54750643], [63.0, -3.07819122, 51.52427984], [64.0, 0.4716213, 51.52161159], [65.0, -2.138815132, 57.1742089], [66.0, -3.3339055, 51.49921789], [67.0, -0.192474902, 51.48511555], [68.0, 0.312917224, 51.4592273], [69.0, 0.165175041, 51.44333737], [70.0, 0.165436907, 51.44355166], [71.0, 0.6902156, 51.44033449], [72.0, -0.0881416, 51.36570379], [73.0, 0.0516055, 51.34658629], [74.0, 0.036362, 51.34532109], [75.0, -1.7589614, 56.5849318], [76.0, -2.950594572, 51.18265582], [77.0, 0.96410185, 50.9143972], [78.0, -1.4746633, 50.90390799], [79.0, -3.3055849, 56.1404298], [80.0, -3.050444102, 55.03199063], [81.0, 1.345638898, 51.30987814], [82.0, -1.49655456, 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543.0, 144.0, 0.828219, -3574.953, 3574.953], [569.0, 499.0, 387.0, 0.01, -1000.0, 1000.0], [570.0, 494.0, 389.0, 0.01, -1400.0, 1400.0], [571.0, 135.0, 501.0, 0.01, -1000.0, 1000.0], [572.0, 409.0, 500.0, 0.01, -1000.0, 1000.0], [573.0, 302.0, 340.0, 0.01, -2250.0, 2250.0], [574.0, 167.0, 491.0, 0.01, -600.0, 600.0], [575.0, 132.0, 495.0, 0.01, -1400.0, 1400.0], [576.0, 261.0, 496.0, 0.01, -2000.0, 2000.0], [577.0, 180.0, 199.0, 0.01, -500.0, 500.0], [578.0, 167.0, 377.0, 0.01, -1200.0, 1200.0], [579.0, 373.0, 497.0, 0.01, -500.0, 500.0], [580.0, 81.0, 498.0, 0.01, -1000.0, 1000.0], [581.0, 69.0, 70.0, 0.01, -4593.493670886076, 4593.493670886076], [582.0, 87.0, 88.0, 0.01, -4593.493670886076, 4593.493670886076], [583.0, 91.0, 92.0, 0.01, -4593.493670886076, 4593.493670886076], [584.0, 96.0, 97.0, 0.01, -4593.493670886076, 4593.493670886076], [585.0, 98.0, 99.0, 0.01, -4593.493670886076, 4593.493670886076], [586.0, 102.0, 103.0, 0.01, -4593.493670886076, 4593.493670886076], [587.0, 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333.0, 334.0, 0.01, -4593.493670886076, 4593.493670886076], [632.0, 338.0, 339.0, 0.01, -4593.493670886076, 4593.493670886076], [633.0, 345.0, 346.0, 0.01, -4593.493670886076, 4593.493670886076], [634.0, 348.0, 349.0, 0.01, -4593.493670886076, 4593.493670886076], [635.0, 351.0, 352.0, 0.01, -4593.493670886076, 4593.493670886076], [636.0, 359.0, 360.0, 0.01, -4593.493670886076, 4593.493670886076], [637.0, 362.0, 363.0, 0.01, -4593.493670886076, 4593.493670886076], [638.0, 365.0, 366.0, 0.01, -4593.493670886076, 4593.493670886076], [639.0, 384.0, 385.0, 0.01, -4593.493670886076, 4593.493670886076], [640.0, 390.0, 391.0, 0.01, -4593.493670886076, 4593.493670886076], [641.0, 398.0, 399.0, 0.01, -4593.493670886076, 4593.493670886076], [642.0, 402.0, 403.0, 0.01, -4593.493670886076, 4593.493670886076], [643.0, 411.0, 412.0, 0.01, -4593.493670886076, 4593.493670886076], [644.0, 420.0, 421.0, 0.01, -4593.493670886076, 4593.493670886076], [645.0, 422.0, 423.0, 0.01, -4593.493670886076, 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-4593.493670886076, 4593.493670886076], [661.0, 132.0, 546.0, 0.01, -4593.493670886076, 4593.493670886076], [662.0, 135.0, 194.0, 0.01, -4593.493670886076, 4593.493670886076], [663.0, 167.0, 168.0, 0.01, -4593.493670886076, 4593.493670886076], [664.0, 180.0, 547.0, 0.01, -4593.493670886076, 4593.493670886076], [665.0, 199.0, 200.0, 0.01, -4593.493670886076, 4593.493670886076], [666.0, 261.0, 548.0, 0.01, -4593.493670886076, 4593.493670886076], [667.0, 302.0, 304.0, 0.01, -4593.493670886076, 4593.493670886076], [668.0, 340.0, 549.0, 0.01, -4593.493670886076, 4593.493670886076], [669.0, 373.0, 550.0, 0.01, -4593.493670886076, 4593.493670886076], [670.0, 377.0, 217.0, 0.01, -4593.493670886076, 4593.493670886076], [671.0, 387.0, 551.0, 0.01, -4593.493670886076, 4593.493670886076], [672.0, 389.0, 316.0, 0.01, -4593.493670886076, 4593.493670886076], [673.0, 409.0, 552.0, 0.01, -4593.493670886076, 4593.493670886076]]) + + self.loads = DataFrame( + ['id', 'bus_id', 'mc_a', 'mc_b', 'mc_c', 'd_max', 'd_min'], + [[1.0, 1.0, 0.0, 0.0, 0.0, 3.243e-05, 3.243e-05], [2.0, 2.0, 0.0, 0.0, 0.0, 0.0007411, 0.0007411], [3.0, 3.0, 0.0, 0.0, 0.0, 0.00110084, 0.00110084], [4.0, 4.0, 0.0, 0.0, 0.0, 0.00098738, 0.00098738], [5.0, 5.0, 0.0, 0.0, 0.0, 0.00036672, 0.00036672], [6.0, 6.0, 0.0, 0.0, 0.0, 0.00084649, 0.00084649], [7.0, 7.0, 0.0, 0.0, 0.0, 0.00111192, 0.00111192], [8.0, 8.0, 0.0, 0.0, 0.0, 0.00143659, 0.00143659], [9.0, 9.0, 0.0, 0.0, 0.0, 0.00106932, 0.00106932], [10.0, 10.0, 0.0, 0.0, 0.0, 0.00105445, 0.00105445], [11.0, 11.0, 0.0, 0.0, 0.0, 0.00015357, 0.00015357], [12.0, 12.0, 0.0, 0.0, 0.0, 2.9e-05, 2.9e-05], [13.0, 13.0, 0.0, 0.0, 0.0, 0.00103458, 0.00103458], [14.0, 14.0, 0.0, 0.0, 0.0, 0.0, 0.0], [15.0, 15.0, 0.0, 0.0, 0.0, 0.00145802, 0.00145802], [16.0, 16.0, 0.0, 0.0, 0.0, 0.00159569, 0.00159569], [17.0, 17.0, 0.0, 0.0, 0.0, 7e-08, 7e-08], [18.0, 18.0, 0.0, 0.0, 0.0, 0.00303935, 0.00303935], [19.0, 19.0, 0.0, 0.0, 0.0, 0.00263215, 0.00263215], [20.0, 20.0, 0.0, 0.0, 0.0, 0.00265858, 0.00265858], [21.0, 21.0, 0.0, 0.0, 0.0, 0.00234459, 0.00234459], [22.0, 22.0, 0.0, 0.0, 0.0, 0.0017222, 0.0017222], [23.0, 23.0, 0.0, 0.0, 0.0, 3.052e-05, 3.052e-05], [24.0, 24.0, 0.0, 0.0, 0.0, 0.0007498, 0.0007498], [25.0, 25.0, 0.0, 0.0, 0.0, 0.00065801, 0.00065801], [26.0, 26.0, 0.0, 0.0, 0.0, 0.00085566, 0.00085566], [27.0, 27.0, 0.0, 0.0, 0.0, 0.00112727, 0.00112727], [28.0, 28.0, 0.0, 0.0, 0.0, 0.00101687, 0.00101687], [29.0, 29.0, 0.0, 0.0, 0.0, 0.00082333, 0.00082333], [30.0, 30.0, 0.0, 0.0, 0.0, 0.00069878, 0.00069878], [31.0, 31.0, 0.0, 0.0, 0.0, 0.00095327, 0.00095327], [32.0, 32.0, 0.0, 0.0, 0.0, 0.00013449, 0.00013449], [33.0, 33.0, 0.0, 0.0, 0.0, 0.00078637, 0.00078637], [34.0, 34.0, 0.0, 0.0, 0.0, 3.77e-06, 3.77e-06], [35.0, 35.0, 0.0, 0.0, 0.0, 0.00230439, 0.00230439], [36.0, 36.0, 0.0, 0.0, 0.0, 0.00102366, 0.00102366], [37.0, 37.0, 0.0, 0.0, 0.0, 0.00138977, 0.00138977], [38.0, 38.0, 0.0, 0.0, 0.0, 0.00189622, 0.00189622], [39.0, 39.0, 0.0, 0.0, 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1.836e-05], [498.0, 498.0, 0.0, 0.0, 0.0, 0.0, 0.0], [499.0, 499.0, 0.0, 0.0, 0.0, 0.0, 0.0], [500.0, 500.0, 0.0, 0.0, 0.0, 5.91e-06, 5.91e-06], [501.0, 501.0, 0.0, 0.0, 0.0, 0.0, 0.0], [502.0, 502.0, 0.0, 0.0, 0.0, 0.00156131, 0.00156131], [503.0, 503.0, 0.0, 0.0, 0.0, 0.00264477, 0.00264477], [504.0, 504.0, 0.0, 0.0, 0.0, 0.00419701, 0.00419701], [505.0, 505.0, 0.0, 0.0, 0.0, 0.00170247, 0.00170247], [506.0, 506.0, 0.0, 0.0, 0.0, 0.00219561, 0.00219561], [507.0, 507.0, 0.0, 0.0, 0.0, 0.00456866, 0.00456866], [508.0, 508.0, 0.0, 0.0, 0.0, 0.00123052, 0.00123052], [509.0, 509.0, 0.0, 0.0, 0.0, 0.00071518, 0.00071518], [510.0, 510.0, 0.0, 0.0, 0.0, 0.00257663, 0.00257663], [511.0, 511.0, 0.0, 0.0, 0.0, 0.00297392, 0.00297392], [512.0, 512.0, 0.0, 0.0, 0.0, 0.00648351, 0.00648351], [513.0, 513.0, 0.0, 0.0, 0.0, 0.00261206, 0.00261206], [514.0, 514.0, 0.0, 0.0, 0.0, 0.00148417, 0.00148417], [515.0, 515.0, 0.0, 0.0, 0.0, 0.00090083, 0.00090083], [516.0, 516.0, 0.0, 0.0, 0.0, 0.00629072, 0.00629072], [517.0, 517.0, 0.0, 0.0, 0.0, 0.00146176, 0.00146176], [518.0, 518.0, 0.0, 0.0, 0.0, 0.00164449, 0.00164449], [519.0, 519.0, 0.0, 0.0, 0.0, 0.00193558, 0.00193558], [520.0, 520.0, 0.0, 0.0, 0.0, 0.00063723, 0.00063723], [521.0, 521.0, 0.0, 0.0, 0.0, 0.00042232, 0.00042232], [522.0, 522.0, 0.0, 0.0, 0.0, 0.00275959, 0.00275959], [523.0, 523.0, 0.0, 0.0, 0.0, 0.00379241, 0.00379241], [524.0, 524.0, 0.0, 0.0, 0.0, 0.00217854, 0.00217854], [525.0, 525.0, 0.0, 0.0, 0.0, 0.00338363, 0.00338363], [526.0, 526.0, 0.0, 0.0, 0.0, 0.0021207, 0.0021207], [527.0, 527.0, 0.0, 0.0, 0.0, 0.00395588, 0.00395588], [528.0, 528.0, 0.0, 0.0, 0.0, 0.00306642, 0.00306642], [529.0, 529.0, 0.0, 0.0, 0.0, 0.00407274, 0.00407274], [530.0, 530.0, 0.0, 0.0, 0.0, 0.00508604, 0.00508604], [531.0, 531.0, 0.0, 0.0, 0.0, 0.00498119, 0.00498119], [532.0, 532.0, 0.0, 0.0, 0.0, 0.00402531, 0.00402531], [533.0, 533.0, 0.0, 0.0, 0.0, 0.00393153, 0.00393153], [534.0, 534.0, 0.0, 0.0, 0.0, 0.00360075, 0.00360075], [535.0, 535.0, 0.0, 0.0, 0.0, 0.00528161, 0.00528161], [536.0, 536.0, 0.0, 0.0, 0.0, 0.00325283, 0.00325283], [537.0, 537.0, 0.0, 0.0, 0.0, 0.00400836, 0.00400836], [538.0, 538.0, 0.0, 0.0, 0.0, 0.00392086, 0.00392086], [539.0, 539.0, 0.0, 0.0, 0.0, 0.00382379, 0.00382379], [540.0, 540.0, 0.0, 0.0, 0.0, 0.00446558, 0.00446558], [541.0, 541.0, 0.0, 0.0, 0.0, 0.00296208, 0.00296208], [542.0, 542.0, 0.0, 0.0, 0.0, 0.00417591, 0.00417591], [543.0, 543.0, 0.0, 0.0, 0.0, 0.00408299, 0.00408299], [544.0, 544.0, 0.0, 0.0, 0.0, 0.00200056, 0.00200056], [545.0, 545.0, 0.0, 0.0, 0.0, 0.00131374, 0.00131374], [546.0, 546.0, 0.0, 0.0, 0.0, 0.00102709, 0.00102709], [547.0, 547.0, 0.0, 0.0, 0.0, 0.0025333, 0.0025333], [548.0, 548.0, 0.0, 0.0, 0.0, 0.00099926, 0.00099926], [549.0, 549.0, 0.0, 0.0, 0.0, 0.00098198, 0.00098198], [550.0, 550.0, 0.0, 0.0, 0.0, 0.00116933, 0.00116933], [551.0, 551.0, 0.0, 0.0, 0.0, 0.0020792, 0.0020792], [552.0, 552.0, 0.0, 0.0, 0.0, 0.00087666, 0.00087666]]) + + self.real_params = True + super().__init__(*args, **kwargs) diff --git a/powergrid_case/transmission/__init__.py b/powergrid_case/transmission/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..2e102c036bbcaeb5e3510f40d0593b3443aca3f3 --- /dev/null +++ b/powergrid_case/transmission/__init__.py @@ -0,0 +1,21 @@ +"""Transmission grid case data.""" + +from .Case5 import Case5 +from .Case14 import Case14 +from .Case118 import Case118 +from .Case300 import Case300 +from .Case29GB import Case29GB +from .Case552GB import Case552GB +from .Case1354pegase import Case1354pegase +from .Case2383wp import Case2383wp + +__all__ = [ + "Case5", + "Case14", + "Case118", + "Case300", + "Case29GB", + "Case552GB", + "Case1354pegase", + "Case2383wp", +]