The platform is built for browsing and exporting renewable energy data. Use the Explore page to filter plants by any combination of fuel type, state, capacity, owner, and data availability — then export the filtered set as CSV or JSON for use in notebooks, dashboards, or analysis pipelines.
Export filtered data for analysis
“I need a structured dataset of US power plants matching specific criteria for my analysis pipeline.”
Build your filter on the Explore page
Apply filters: fuel type, state, capacity range, operating status, owner, and data availability toggles (has generation, has pricing, has financial data). The KPI bar updates in real time to show the count and total capacity of matched plants.
Verify in the table and map
Sort the table by any column. Toggle columns on/off to see the fields you need. Check the map to confirm geographic distribution. This is your quality check before exporting.
Export as CSV or JSON
Click the Export button in the table toolbar. Choose CSV for spreadsheet and pandas workflows, or JSON for programmatic use. The export includes all visible columns plus plant IDs.
# Load the exported file in Python
import pandas as pd
df = pd.read_csv("renewablesinfo_2026-03-20.csv")
print(f"{len(df)} plants, {df['capacity_mw'].sum():.0f} MW total")Save the shareable URL
Copy the browser URL — it encodes the exact filter state. Bookmark it, share it with collaborators, or include it in your research methodology. When you revisit the URL, the same filters are restored with the latest data.
Key insight
The Explore page lets you build precise filters visually, verify the results in the table and map, then export the exact dataset you need. Shareable URLs encode the full filter state — include them in your methodology for reproducibility.
Get data for bulk or programmatic access
“I need larger datasets, automated pipelines, or integration with my own systems.”
Start with what's available
The Explore page export handles most one-off analysis needs. You can export up to the full plant index (>15,000 plants) as CSV or JSON with a single click.
Contact us for deeper needs
For bulk data access, automated pipelines, custom data formats, or partnership inquiries, get in touch:
Tell us about your use case — we're actively building data access capabilities and your input shapes the roadmap.
Explore the open-source codebase
The entire platform is open-source. If you're a developer interested in how the data pipeline works — from raw EIA/FERC sources through enrichment to the final dataset — the code and documentation are available on GitHub.
Key insight
The platform is open-source and designed for transparency. For bulk data access, custom exports, or partnership inquiries, reach out directly — we're building toward broader programmatic access and want to understand what researchers and developers need.
What's coming
Planned
A public data API with stable endpoints and documentation. Time-series generation data exports. Expanded export formats including Parquet for large datasets.
Exploring
A Python SDK for programmatic access with pandas-native return types. Webhook notifications for data changes. Bulk download packages for offline analysis.