US Net (Residual) Load
US residual load - demand minus wind and solar generation - per EIA region and hour. The curve dispatchable plants and batteries chase; pre-aligned from EIA demand + generation.
- Source
- derived
- Licence
- Redistributable open data
- Updates
- Intraday
- Data through
- 2026-07-31
- Quality
- QC clean · 0 failures
- Format
- Apache Parquet + dictionary
Safe to train on
Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.
What's included
- US net (residual) load = demand - wind - solar, 13 regions, 2021-present
- Derived + aligned from EIA demand + generation-by-fuel
- Negative values preserved (renewable surplus)
- Source: U.S. Energy Information Administration (public domain)
Schema
| Column | Type | Description | Filled | Distinct |
|---|---|---|---|---|
| zone | str | EIA region | 100.0% | 13 |
| ts | timestamp (UTC) | Hour | 100.0% | 48,895 |
| net_load_mwh | float | Demand - wind - solar, MWh | 100.0% | 94,906 |
| unit | str | Unit | 100.0% | 1 |
| res_min | int | Native resolution (hourly) | 100.0% | 1 |
Sample & preview
Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: derived (redistributable open data; attribution passes through - see our Licence).
Don't trust screenshots - drop the sample into your notebook right now.
import pandas as pd df = pd.read_parquet("us-net-load_sample.parquet") df.info() # typed columns, gap-aware, ready to join⬇ Download free Parquet sample or CSV for Excel
Coverage: 13 zones
CAL · CAR · CENT · FLA · MIDA · MIDW · NE · NW · NY · SE · SW · TEN · TEX
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