Data related to "Assess Space-Based Solar Power for European-Scale Power System Decarbonization"

This is the accompanying dataset for the publication "Assess Space-Based Solar Power for European-Scale Power System Decarbonization". The dataset contains the following input data files: powerplants.csv: power plant-level technical and geographic information used to build generator inputs for the PyPSA-Eur model, including fuel type, capacity, location, efficiency and commissioning year electricity_demand.csv: hourly electricity demand per country for a full year, used by the PyPSA-Eur model, in MW europe-2020-era5.nc: hourly weather-based capacity factors for renewable energy technologies per country and technology, derived from ERA5 reanalysis data, used by the PyPSA-Eur model, in per unit (p.u.) sbsp_rd1(rd2)_profile_2020.nc: hourly normalized generation profiles for RD1 or RD2 SBSP configurations in 2020, representing power output as a fraction of maximum generation, used by the PyPSA-Eur model, in per unit (p.u.) sbsp_rd1(rd2)_profile_2050.nc: hourly normalized generation profiles for RD1 or RD2 SBSP configurations in 2050, representing power output as a fraction of maximum generation, used by the PyPSA-Eur model, in per unit (p.u.) costs.csv: cost assumptions, used by the PyPSA-Eur model, units defined in units column resources/: geospatial and technology-specific input data used by the PyPSA-Eur model, including regional boundaries, renewable generation profiles, spatial constraints, and power plant reference data The dataset contains the intermediate output data files: elec_s_37_ec_lcopt_Co2L0.7-3H.nc: PyPSA-Eur network for the year 2020 generated before integrating SBSP, containing techno-economic model outputs including capacities, flows, and costs elec_s_37_ec_lcopt_Co2L0.0-3H_maximum.nc: PyPSA-Eur network for the year 2050 assuming maximum projected technology costs for all generation technologies elec_s_37_ec_lcopt_Co2L0.0-3H_minimum.nc: PyPSA-Eur network for the year 2050 assuming minimum projected technology costs for all generation technologies elec_s_37_ec_lcopt_Co2L0.0-3H.nc: PyPSA-Eur network for the year 2050 assuming average projected technology costs for all generation technologies The dataset contains the result data files from PyPSA-Eur model runs with integrated SBSP under various scenario settings. Each folder corresponds to a specific combination of scenario year (e.g. 2020, 2050) and SBSP annual fixed cost (capital cost). All results reflect optimized power system configurations with SBSP included. The following files are provided as examples from the "2050_RD1_267869" scenario, which represents the year 2050 with RD1 (SBSP) assumed to have a annual fixed cost of 267869 EUR/MW-year: optimized_2050_rd1_267869_network.nc: Optimized PyPSA-Eur network for 2050 with integrated RD1 2050_middle_rd1_hourly_energy_supply.csv: Hourly energy supply by technology in the optimized network, in MW 2050_middle_rd1_optimization_output.txt: Full solver output from the optimization process 2050_middle_rd1_statistics_cleaned.csv: Aggregated statistics of key components in the network active_rd1_SBSP_buses.txt: List of buses (nodes) where SBSP is actively installed generators_2050_rd1_267869.csv: Detailed parameters of all generators in the optimized network storage_units_2050_rd1_267869.csv: Detailed parameters of all storage units stores_2050_rd1_267869.csv: Detailed parameters of all stores sbsp_rd1_p_nom_opt_results.csv: Optimized SBSP installed capacity per node, in MW Each folder follows the same structure, with file names indicating the year and SBSP annual fixed cost. These results support analysis of SBSP deployment under varying techno-economic assumptions.