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Research & Policy

Research workflows: analyzing technology trends, exporting data for notebooks, and using shareable URLs as data sources.

Academic ResearcherPolicy AnalystThink Tank

The platform is designed for researchers who need structured, exportable data on US power plants. Filter to any subset, export as CSV or JSON, and use shareable URLs as citation-ready references to your exact dataset.

How has solar panel technology evolved — fixed-tilt vs single-axis tracking, crystalline silicon vs thin-film?

1

Filter to solar

On the Explore page, set Fuel Type = Solar, Status = Operating. The KPI bar shows the total count and capacity.

2

Export the filtered set

Click the export button and choose JSON or CSV. The export includes all columns visible in the table plus additional metadata.

3

Load in a notebook

In Python/pandas, load the exported file. Group by operating year and technology to see trends.

import pandas as pd
df = pd.read_csv("renewablesinfo_solar_operating.csv")
trends = df.groupby(["operating_year", "technology"]).agg(
    plants=("plant_id", "count"),
    total_mw=("capacity_mw", "sum")
).reset_index()
4

Drill into engineering specs

Click any solar plant on the Explore table. In the Engineering section, see generator cards with panel specs: tracking type, tilt/azimuth, bifacial, module technology, and USPVDB site classification.

Topaz Solar Farm generator detail — tracking type, panel material, tilt/azimuth, and USPVDB satellite project data

Key insight

USPVDB integration gives panel-level specifications for 75% of solar generators — tracking type, module technology, tilt angle, bifacial adoption, and even site classification (brownfield, agrivoltaic, landfill). This granularity is unavailable from EIA alone.

Study wind turbine evolution and repowering

How have wind turbine specifications changed over time? Which plants have been repowered?

1

Filter to wind

On the Explore page, set Fuel Type = Wind. Export the full set for analysis if needed.

2

Check turbine specs

Click any wind plant. The Engineering section shows individual turbine cards with hub height (m), rotor diameter (m), manufacturer, model, and capacity. If the plant has been repowered, you'll see a “Retrofit Year” field on the updated turbines.

Alta Wind X generator detail — 45 turbines, GE Wind GE2.85-103, rotor 103m, hub 85m, 2850 kW per turbine, 45 mapped locations
3

View turbine locations on the map

On the plant detail page map, toggle the “Turbine Locations” layer. Individual turbine positions from USWTDB appear as dots on the map — useful for layout analysis and visual verification.

Key insight

USWTDB provides individual turbine data for 76,000+ turbines: manufacturer, model, hub height, rotor diameter, and retrofit year. Plants that have been repowered show different vintage turbines at the same site — visible in the generator cards and on the map.

Export data for external analysis

I need a clean dataset of all operating solar plants in California with generation data for a research paper.

1

Build your filter

On the Explore page: Fuel = Solar, State = CA, Status = Operating, Data Availability = Has Generation. The KPI bar confirms the count and total capacity.

2

Verify before exporting

Scan the table. Sort by capacity to ensure the expected large plants appear. Check that the count matches your expectations.

3

Export and use the URL

Export as CSV for immediate use. Copy the browser URL — it encodes the exact filter state. This URL is your citation-ready data source.

4

Cite and share the URL

The shareable URL encodes the full filter state. Include it in your paper's methodology section — reviewers can click the link and see the exact dataset with the latest data. For programmatic or bulk data access, contact hi@renewablesinfo.org.

Key insight

Every filter combination produces a shareable URL. Share it in your methodology section and reviewers can reproduce the exact dataset. Filter, verify, export — then cite the URL for reproducibility.

The platform refreshes monthly from federal sources (EIA, FERC, LBNL). Shareable URLs always reflect the latest data — your citation stays current without manual updates. As new sources are integrated, engineering specs and generation coverage deepen automatically.

What's coming

Planned

Time-series generation data export — monthly MWh and capacity factor as downloadable CSV per plant or for filtered sets. Expanded export formats including Parquet for large datasets.

Exploring

Citation-ready data packages with DOI-linked versioned snapshots. A public data API for programmatic access. Natural language queries — ask questions like “total solar capacity in Texas by year” and get structured results without building filters manually. Interested in these features? Let us know.