Abstract
<jats:p>Abstract. We present CERFRES (CERRA-derived Farm-level Renewable Energy Systems generation for Europe), a physics-based modeling framework for simulating hourly renewable energy generation from utility-scale and distributed wind and solar installations across Europe. The framework combines generator-level metadata with the high-resolution Copernicus European Regional ReAnalysis (CERRA, 5.5 × 5.5 km) to convert local meteorological conditions into per-plant power output via physically motivated models for wind speed extrapolation, multi-turbine power aggregation, and photovoltaic performance. The resulting time series span the 1995–2025 period at the individual asset level, alongside national and bidding-zone aggregations, covering 8,203 wind farms and 22,190 solar PV installations. Because historical generation records at individual plant level are rarely disclosed by transmission system operators or plant owners, a validated open-access modeling framework capable of reproducing sub-national variability provides critical infrastructure for power-system research. Validation against ENTSO-E reported actual generation demonstrates strong temporal agreement across Europe; solar PV modeling achieves Pearson correlation coefficients exceeding 0.95 in most major national markets. A case-study farm-level validation against 61 Norwegian onshore wind farms for January 2023 yields correlation coefficients of 0.78–0.93 at individual plant level, indicating that the 5.5 km meteorological forcing can resolve sub-national variability. Benchmarking against EMHIRES and Renewables Ninja, two widely used open-access European renewable generation datasets, shows country-mean normalized RMSE reductions for solar PV of 31 % and 37 %, with corresponding normalized MAE reductions of 34 % and 39 %, over the commonly covered countries.</jats:p>