Estimating Power Plant Generation in the Global Power Plant Database

This technical note describes the methodology used to estimate annual electricity generation for power plants within the Global Power Plant Database, utilizing a combination of statistical regression and machine learning.

• The Global Power Plant Database employs estimation models for annual electricity generation based on fuel types, specifically for wind, solar, hydropower (hydro), and gas plants. The approach integrates machine learning with statistical regression, using variables such as plant size, fuel type, and country-specific average generation per megawatt of installed capacity.
• Fuel-specific models increase the accuracy of generation estimates for hydropower, solar, and wind plants. While estimates for natural gas plants also show improvement, they continue to have high error rates, particularly for smaller facilities.

APA

World Resources Institute (n.d.). Estimating Power Plant Generation in the Global Power Plant Database. https://www.wri.org/research/estimating-power-plant-generation-global-power-plant-database

Chicago

World Resources Institute. Estimating Power Plant Generation in the Global Power Plant Database. n.d. https://www.wri.org/research/estimating-power-plant-generation-global-power-plant-database.

Wikipedia

{{cite report |author=World Resources Institute |title=Estimating Power Plant Generation in the Global Power Plant Database |url=https://www.wri.org/research/estimating-power-plant-generation-global-power-plant-database |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{worldresourcesinstitutendestimating, author = {{World Resources Institute}}, title = {{Estimating Power Plant Generation in the Global Power Plant Database}}, institution = {World Resources Institute}, url = {https://www.wri.org/research/estimating-power-plant-generation-global-power-plant-database}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }