Datasets:

solsticestudioai
/

solstice-residential-energy-pack

@@ -1,156 +1,155 @@
----
-license: cc-by-4.0
-task_categories:
-  - tabular-classification
-  - tabular-regression
-  - time-series-forecasting
-language:
-  - en
-tags:
-  - synthetic
-  - energy
-  - solar
-  - battery
-  - residential-energy
-  - vpp
-  - virtual-power-plant
-  - distributed-energy
-  - tariff-modeling
-  - outage-resilience
-  - analytics
-  - tabular
-pretty_name: Solstice Residential Energy Pack
-size_categories:
-  - 100K<n<1M
-configs:
-  - config_name: households
-    data_files:
-      - split: train
-        path: households.csv
-  - config_name: daily_generation_consumption
-    data_files:
-      - split: train
-        path: daily_generation_consumption.csv
-  - config_name: dispatch_events
-    data_files:
-      - split: train
-        path: dispatch_events.csv
-  - config_name: billing_and_savings
-    data_files:
-      - split: train
-        path: billing_and_savings.csv
-  - config_name: metric_definitions
-    data_files:
-      - split: train
-        path: metric_definitions.csv
-  - config_name: dashboard_suggestions
-    data_files:
-      - split: train
-        path: dashboard_suggestions.csv
----
-# Solstice Residential Energy Pack (Sample)
-**A synthetic residential solar-plus-storage operations dataset for VPP dispatch, tariff-aware savings, billing, and outage resilience.** This sample is designed for product demos, analytics workflows, dashboard prototyping, and AI model validation where real customer or utility data is unavailable or too sensitive to use.
-Built by [SolsticeAI](https://www.solsticestudio.ai) as a free sample of a larger commercial pack. 100% synthetic. No real customer, meter, or utility records.
-## What is included
-| File | Rows | Grain | Purpose |
-|---|---:|---|---|
-| `households.csv` | 500 | household | Household archetypes, geography, electrification, and outage risk |
-| `daily_generation_consumption.csv` | 90,000 | date x household | Load, solar generation, import/export, battery usage, and daily savings |
-| `dispatch_events.csv` | 5,819 | dispatch event | Requested vs delivered dispatch, participation, incentives, and grid value |
-| `billing_and_savings.csv` | 3,000 | month x household | Counterfactual bills, subscription payments, credits, and net customer value |
-| `metric_definitions.csv` | 3 | metric | Metric formulas and table-level documentation |
-| `dashboard_suggestions.csv` | 3 | chart | Starter dashboard recipes for product and analytics teams |
-**Coverage:** USA
-**Period:** 6 months (`2025-01-01` to `2025-06-29`)
-**Join key:** `household_id`
-**Formats in this sample repo:** CSV
-## Why this dataset is useful
-Most public solar or energy datasets are either too generic, too narrow, or detached from the operating model of a residential energy business. This sample is shaped around the questions a solar-plus-storage platform, VPP operator, DERMS vendor, or energy analytics team actually cares about:
-- Which household profiles create the highest dispatch value?
-- How much do tariff design and load shape affect savings?
-- Which homes deliver the most outage resilience value?
-- How reliable is dispatch participation across a residential fleet?
-- How do billing, credits, and contract economics affect customer value?
-## What makes the sample credible
-- Stable relational keys and business-readable tables
-- Daily operational energy facts rather than flat summary rows
-- Dispatch, billing, and savings data tied to the same household base
-- Structured for dashboarding, workflow testing, demos, and model development
-- Synthetic by design, so it can be shared safely across internal and external teams
-## Typical use cases
-- Residential energy product demos
-- VPP dispatch and participation analytics
-- Tariff-aware savings analysis
-- Billing workflow and customer-value testing
-- Outage resilience reporting
-- AI model validation on structured energy operations data
-- Dashboard and BI template development
-## Quick start
-```python
-import pandas as pd
-households = pd.read_csv("households.csv")
-daily = pd.read_csv("daily_generation_consumption.csv", parse_dates=["date"])
-dispatch = pd.read_csv("dispatch_events.csv", parse_dates=["date"])
-billing = pd.read_csv("billing_and_savings.csv")
-# Example: average savings by state
-savings_by_state = (
-    daily.merge(households[["household_id", "state"]], on="household_id", how="left")
-         .groupby("state")["customer_savings_usd"]
-         .mean()
-         .reset_index()
-)
-```
-## Schema
-See [SCHEMA.md](./SCHEMA.md) for the full field definitions and pack design.
-See `manifest.json` for sample generation metadata and row counts.
-## License
-Released under **CC BY 4.0**. Use freely for demos, internal tooling, research, education, and commercial prototyping with attribution.
-Synthetic data only. No real customer, patient, meter, or utility information.
-## Get the full pack
-This Hugging Face repo is a **500-household, 6-month sample**. The production pack scales to 5,000–25,000+ households, 12+ month historical windows, additional tables (tariffs, outage events, service tickets, contracts, installations, enrollment, portfolio KPIs), CSV and Parquet delivery, and buyer-specific variants.
-**Self-serve (Stripe checkout):**
-- [**Sample Scale tier — $5,000**](https://buy.stripe.com/7sY5kD2j85QTfSb5lfeEo03) — ~25K records, one subject, 72-hour delivery.
-**Full pack + enterprise scope:**
-- [www.solsticestudio.ai/datasets](https://www.solsticestudio.ai/datasets) — per-SKU pricing across Starter / Professional / Enterprise tiers.
-- [www.solsticestudio.ai/datasets](https://www.solsticestudio.ai/contact) — discovery call for commercial licensing, custom generation, or buyer-specific variants.
-**Procurement catalog:**
-- [SolsticeAI Data Storefront](https://solsticeai.mydatastorefront.com) — available via Datarade / Monda.
-## Citation
-```bibtex
-@dataset{solstice_residential_energy_pack_2026,
-  title        = {Solstice Residential Energy Pack (Sample)},
-  author       = {SolsticeAI},
-  year         = {2026},
-  publisher    = {Hugging Face},
-  url          = {https://huggingface.co/datasets/solsticestudioai/solstice-residential-energy-pack}
-}
-```

+---
+license: cc-by-4.0
+task_categories:
+  - tabular-classification
+  - tabular-regression
+  - time-series-forecasting
+language:
+  - en
+tags:
+  - synthetic
+  - energy
+  - solar
+  - battery
+  - residential-energy
+  - vpp
+  - virtual-power-plant
+  - distributed-energy
+  - tariff-modeling
+  - outage-resilience
+  - analytics
+  - tabular
+pretty_name: Solstice Residential Energy Pack
+size_categories:
+  - 100K<n<1M
+configs:
+  - config_name: households
+    data_files:
+      - split: train
+        path: households.csv
+  - config_name: daily_generation_consumption
+    data_files:
+      - split: train
+        path: daily_generation_consumption.csv
+  - config_name: dispatch_events
+    data_files:
+      - split: train
+        path: dispatch_events.csv
+  - config_name: billing_and_savings
+    data_files:
+      - split: train
+        path: billing_and_savings.csv
+  - config_name: metric_definitions
+    data_files:
+      - split: train
+        path: metric_definitions.csv
+  - config_name: dashboard_suggestions
+    data_files:
+      - split: train
+        path: dashboard_suggestions.csv
+---
+# Solstice Residential Energy Pack (Sample)
+**A synthetic residential solar-plus-storage operations dataset for VPP dispatch, tariff-aware savings, billing, and outage resilience.** This sample is designed for product demos, analytics workflows, dashboard prototyping, and AI model validation where real customer or utility data is unavailable or too sensitive to use.
+Built by [SolsticeAI](https://www.solsticestudio.ai/datasets) as a free sample of a larger commercial pack. 100% synthetic. No real customer, meter, or utility records.
+## What is included
+| File | Rows | Grain | Purpose |
+|---|---:|---|---|
+| `households.csv` | 500 | household | Household archetypes, geography, electrification, and outage risk |
+| `daily_generation_consumption.csv` | 90,000 | date x household | Load, solar generation, import/export, battery usage, and daily savings |
+| `dispatch_events.csv` | 5,819 | dispatch event | Requested vs delivered dispatch, participation, incentives, and grid value |
+| `billing_and_savings.csv` | 3,000 | month x household | Counterfactual bills, subscription payments, credits, and net customer value |
+| `metric_definitions.csv` | 3 | metric | Metric formulas and table-level documentation |
+| `dashboard_suggestions.csv` | 3 | chart | Starter dashboard recipes for product and analytics teams |
+**Coverage:** USA
+**Period:** 6 months (`2025-01-01` to `2025-06-29`)
+**Join key:** `household_id`
+**Formats in this sample repo:** CSV
+## Why this dataset is useful
+Most public solar or energy datasets are either too generic, too narrow, or detached from the operating model of a residential energy business. This sample is shaped around the questions a solar-plus-storage platform, VPP operator, DERMS vendor, or energy analytics team actually cares about:
+- Which household profiles create the highest dispatch value?
+- How much do tariff design and load shape affect savings?
+- Which homes deliver the most outage resilience value?
+- How reliable is dispatch participation across a residential fleet?
+- How do billing, credits, and contract economics affect customer value?
+## What makes the sample credible
+- Stable relational keys and business-readable tables
+- Daily operational energy facts rather than flat summary rows
+- Dispatch, billing, and savings data tied to the same household base
+- Structured for dashboarding, workflow testing, demos, and model development
+- Synthetic by design, so it can be shared safely across internal and external teams
+## Typical use cases
+- Residential energy product demos
+- VPP dispatch and participation analytics
+- Tariff-aware savings analysis
+- Billing workflow and customer-value testing
+- Outage resilience reporting
+- AI model validation on structured energy operations data
+- Dashboard and BI template development
+## Quick start
+```python
+import pandas as pd
+households = pd.read_csv("households.csv")
+daily = pd.read_csv("daily_generation_consumption.csv", parse_dates=["date"])
+dispatch = pd.read_csv("dispatch_events.csv", parse_dates=["date"])
+billing = pd.read_csv("billing_and_savings.csv")
+# Example: average savings by state
+savings_by_state = (
+    daily.merge(households[["household_id", "state"]], on="household_id", how="left")
+         .groupby("state")["customer_savings_usd"]
+         .mean()
+         .reset_index()
+)
+```
+## Schema
+See [SCHEMA.md](./SCHEMA.md) for the full field definitions and pack design.
+See `manifest.json` for sample generation metadata and row counts.
+## License
+Released under **CC BY 4.0**. Use freely for demos, internal tooling, research, education, and commercial prototyping with attribution.
+Synthetic data only. No real customer, patient, meter, or utility information.
+## Get the full pack
+This Hugging Face repo is a **500-household, 6-month sample**. The production pack scales to 5,000–25,000+ households, 12+ month historical windows, additional tables (tariffs, outage events, service tickets, contracts, installations, enrollment, portfolio KPIs), CSV and Parquet delivery, and buyer-specific variants.
+**Self-serve (Stripe checkout):**
+- [**Sample Scale tier — $5,000**](https://buy.stripe.com/7sY5kD2j85QTfSb5lfeEo03) — ~25K records, one subject, 72-hour delivery.
+**Full pack + enterprise scope:**
+- [www.solsticestudio.ai/datasets](https://www.solsticestudio.ai/datasets) — per-SKU pricing across Starter / Professional / Enterprise tiers, plus commercial licensing, custom generation, and buyer-specific variants.
+**Procurement catalog:**
+- [SolsticeAI Data Storefront](https://solsticeai.mydatastorefront.com) — available via Datarade / Monda.
+## Citation
+```bibtex
+@dataset{solstice_residential_energy_pack_2026,
+  title        = {Solstice Residential Energy Pack (Sample)},
+  author       = {SolsticeAI},
+  year         = {2026},
+  publisher    = {Hugging Face},
+  url          = {https://huggingface.co/datasets/solsticestudioai/solstice-residential-energy-pack}
+}
+```