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---

license: cc-by-4.0
task_categories:
  - time-series-forecasting
  - tabular-regression
  - reinforcement-learning
language:
  - en
tags:
  - synthetic
  - energy
  - vpp
  - virtual-power-plant
  - derms
  - smart-grid
  - solar
  - battery-storage
  - utilities
pretty_name: Solstice Residential Energy (VPP) Pack
size_categories:
  - 1K<n<10K
configs:
  - config_name: battery_systems
    data_files:
      - split: train
        path: data/battery_systems/train.csv
  - config_name: billing_and_savings
    data_files:
      - split: train
        path: data/billing_and_savings/train.csv
  - config_name: channel_attribution
    data_files:
      - split: train
        path: data/channel_attribution/train.csv
  - config_name: daily_generation_consumption
    data_files:
      - split: train
        path: data/daily_generation_consumption/train.csv
  - config_name: dashboard_suggestions
    data_files:
      - split: train
        path: data/dashboard_suggestions/train.csv
  - config_name: dispatch_events
    data_files:
      - split: train
        path: data/dispatch_events/train.csv
  - config_name: households
    data_files:
      - split: train
        path: data/households/train.csv
  - config_name: installation_pipeline
    data_files:
      - split: train
        path: data/installation_pipeline/train.csv
  - config_name: metric_definitions
    data_files:
      - split: train
        path: data/metric_definitions/train.csv
  - config_name: outage_events
    data_files:
      - split: train
        path: data/outage_events/train.csv
  - config_name: portfolio_kpis_daily
    data_files:
      - split: train
        path: data/portfolio_kpis_daily/train.csv
  - config_name: service_tickets
    data_files:
      - split: train
        path: data/service_tickets/train.csv
  - config_name: solar_systems
    data_files:
      - split: train
        path: data/solar_systems/train.csv
  - config_name: subscriber_contracts
    data_files:
      - split: train
        path: data/subscriber_contracts/train.csv
  - config_name: utility_tariffs
    data_files:
      - split: train
        path: data/utility_tariffs/train.csv
  - config_name: vpp_program_enrollment
    data_files:
      - split: train
        path: data/vpp_program_enrollment/train.csv
---


# Solstice Residential Energy (VPP) Pack (Sample)

**A high-fidelity synthetic dataset for residential energy transition and VPP operations.** This dataset simulates the lifecycle of residential solar and battery systems, including installation pipelines, daily generation/consumption telemetry, and Virtual Power Plant (VPP) dispatch events.

Built by [Solstice AI Studio](https://www.solsticestudio.ai/datasets) as a free sample of a larger commercial pack. 100% synthetic — no real household or utility data.

## What's in the box

This dataset consists of 16 interconnected tables covering:
- **Asset Dimensions:** `households`, `solar_systems`, `battery_systems`, `utility_tariffs`
- **Telemetry Fact Tables:** `daily_generation_consumption`
- **Operational Events:** `outage_events`, `dispatch_events`, `service_tickets`
- **VPP & Commercial:** `subscriber_contracts`, `vpp_program_enrollment`, `billing_and_savings`
- **Growth & Marketing:** `installation_pipeline`, `channel_attribution`

## Use Cases
- **VPP Optimization:** Train RL agents to optimize battery dispatch during grid stress events.
- **Grid Stability Research:** Model the impact of residential solar/storage on simulated grid outages.
- **Customer Analytics:** Identify high-propensity households for VPP enrollment based on usage patterns.
- **Financial Modeling:** Simulate savings and ROI for residential solar portfolios under different tariff structures.

## Data Provenance
Generated using Solstice’s PhantasOS / SIMA simulation engine. The simulation models physics-aligned generation (based on simulated weather seeds) and realistic household load profiles, alongside commercial contract logic.

## Get the Full Pack
Scale this dataset to 100K+ households, multiple utility regions, and high-resolution (15-min) telemetry.
[www.solsticestudio.ai/datasets](https://www.solsticestudio.ai/datasets)