Renewable Capacity By Country Excel Data: Dataset Structure and Field Coverage

The export menu is why spreadsheet-first analysts start here. Every table page offers an output-format dropdown with two on-screen layouts, a PX-file, tab-, comma-, space- or semicolon-delimited CSV with heading, and native Excel (.xlsx). Choose xlsx and the result opens as a pivot-ready grid: one row per country/area, technology, grid-connection and year combination, with capacity expressed in megawatts.

IRENASTAT's wizard produces a usable workbook in one pass if the dimension choices are made deliberately:

Of the 15 primary datasets Datadory catalogs for Renewable Electricity - a pool averaging 8.0 of 10 on quality against a catalog-wide 7.81 - six carry the country-capacity workload. They differ less in coverage than in shape: official statistics ship long-format country-year panels, asset trackers ship facility rows you aggregate yourself, and the IEA dashboard mixes history with scenario values. The comparison fixes each source to what actually lands in the spreadsheet.

Pivot the Global Energy Monitor trackers from phase rows to country totals and the scale of the installed base falls out immediately. The Global Solar Power Tracker holds 103,940 utility-scale solar phases totaling 2,093 GWac operating, with another 2,247 GWac prospective - and because every operating phase of 1 MW and above is listed individually, a PivotTable on the Country/Area and Status columns rebuilds any national fleet in seconds. Distributed solar below 1 MW is aggregated for 31 countries/areas rather than listed, so a country pivot captures utility-scale capacity only in those places.

The Global Wind Power Tracker behaves the same way for wind: 32,227 phases across 166 countries and areas, comprehensive above 10 MW, separating 1,129 GW operating from 2,656 GW prospective. Its seven summary tables - already viewable as Google Sheets without registration - publish capacity by country/area, new capacity added by country/year and prospective capacity by country/year, which is the fastest pre-aggregated cross-check on a hand-built pivot.

For direction of travel, the IEA Renewables Data Explorer's market series carries Capacity, Generation and Net additions flows across 76 selectable regions and countries from 2000 out to 2030. Generation-side companions - OWID's renewables_electricity column in TWh or the World Bank's percentage-share indicator - measure output rather than megawatts, so pair them with a capacity table instead of substituting one.

Five failure modes turn a clean export into a wrong model.

First, aggregation rows. IRENASTAT's 226 country/area selections include aggregates such as Eurasia and Oceania, and the World Bank's roughly 266 entities include regional and income aggregates alongside countries - filter to individual countries before totalling.

Second, dimension double counting. Selecting both OnGrid and OffGrid duplicates every technology row, and IRENASTAT's technology list mixes renewables with non-renewable comparators and Pumped hydro, so filter to Total renewable energy or named technologies.

Third, status mixing. GEM's Status column separates operating from prospective phases; summing them books 2,247 GWac of unbuilt solar as if it were running.

Fifth, format friction. DESNZ publishes no CSV variants - roughly 15 core workbooks ranging from about 30 KB to 450 KB arrive as XLSX and ODS on each monthly refresh - and its de-rated capacity column applies fixed factors of 0.365 for hydro, 0.43 for wind and 0.17 for solar PV, a UK accounting convention rather than a transferable capacity factor.