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

This is the accompanying dataset for the publication "Assess Space-Based Solar Power in 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 capital cost (in EUR/MW). 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 capital cost of 267869 EUR/MW:

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 capital cost. These results support analysis of SBSP deployment under varying techno-economic assumptions.