Regional Wind Power Profiles for the PLANtoACT Project Description This dataset contains normalized hourly wind power generation profiles developed for the PLANtoACT project (Task 2.2). The profiles represent the long-term wind generation behaviour of five European pilot regions and are intended for use in energy system modelling, renewable energy assessment, and regional energy planning. The dataset was generated using the Renewables.ninja API together with regional administrative boundaries. Hourly wind power time series were downloaded for multiple MERRA-2 grid points located within each region, aggregated into representative regional profiles, and normalized while preserving the long-term equivalent full-load hours (Heq). The dataset accompanies the scripts available in the corresponding GitLab repository. Study Regions The dataset contains wind generation profiles for the following regions: Country Region Italy Lombardia Romania Alba Germany Oberland France Auvergne-Rhône-Alpes Portugal Porto Metropolitan Area Dataset Structure Each regional folder contains: File Description profile_final_8760h.csv Final normalized hourly wind profile for a standard (8760-hour) year profile_final_8784h.csv Final normalized hourly wind profile for a leap (8784-hour) year profile_final_8760h.txt Plain-text version of the 8760-hour profile profile_final_8784h.txt Plain-text version of the 8784-hour profile profile_aggregated_normalised.csv Aggregated multi-year normalized profile before correction heq_by_year.csv Equivalent full-load hours calculated for each simulated year grid_map.png MERRA-2 grid points used for the regional aggregation heq_comparison.png Comparison of annual equivalent full-load hours profile_final_plot.png Visualization of the final normalized profile The dataset also includes Normalized_Profiles_wind_2024.png which compares the normalized wind generation profiles across all study regions. Data Generation Methodology The regional wind profiles were generated according to the following workflow: Regional administrative boundaries were provided as GIS shapefiles. MERRA-2 grid points falling within each regional polygon were identified. Hourly wind power capacity factors were downloaded from the Renewables.ninja API for each grid point over a five-year period (2020–2024). Hourly time series from all selected grid points were aggregated to produce a representative regional profile. Annual equivalent full-load hours (Heq) were calculated for each grid point and for the aggregated profile. The aggregated profile was normalized using the maximum observed generation. A non-linear correction factor was applied to the most recent year (2024) to preserve the long-term average annual energy production while maintaining the hourly variability. Final normalized hourly profiles were exported for both standard (8760-hour) and leap-year (8784-hour) calendars. Data Format The profile files contain a single column: Column Description normalised Hourly normalized wind power generation (dimensionless, ranging from 0 to 1) Each row represents one hour of the year. The annual energy production can be reconstructed by multiplying the normalized profile by the corresponding regional maximum capacity factor. Intended Applications The dataset is intended for: Energy system modelling Renewable energy scenario analysis Regional energy planning Capacity expansion modelling Long-term electricity system simulations Sector coupling studies Academic research Software The dataset was generated using Python together with the following libraries: pandas NumPy GeoPandas Shapely SciPy Matplotlib Requests Hourly wind generation data were obtained using the Renewables.ninja API. Related Software The scripts used to generate this dataset are available from the associated GitLab repository: PLANtoACT Task 2.2 – Regional Wind Power Profile Generation Funding This work was developed within the PLANtoACT project. The PLANtoACT project has received funding from the European Union's LIFE Programme under Grant Agreement No. 101214506 (LIFE-2024-CET), managed by the European Climate, Infrastructure and Environment Executive Agency (CINEA). Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor CINEA can be held responsible for them. Authors Matteo Giacomo Prina Valentina D'Alonzo Citation If you use this dataset in your work, please cite both the Zenodo record and the associated software repository: PLANtoACT / task_2_1 / Wind Power Hourly Profiles · GitLab.