Optimizing renewable energy siting in the Swiss landscape

This study examines the siting scenarios for renewable energy infrastructure (REI) in Switzerland, incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed. MARXAN was run for 2 versions: a) without ground-mounted open space PV infrastructure (excl. OS) and b) with ground-mounted open space PV infrastructure (incl. OS). In each version optimization was done using ecological costs (ECUess) or social costs (ECUsoc) in a regular grid of 4x4km (planning unit). File: PU_data.shp: compressed Shapefile (ESRI) from the MARXAN optimization with 2216 rows (objects) and 18 columns (variables) with sf (simple feature) and data frame classes. Headers are described below: X01 = Planning_units (PUs) X02 = incl.OS. number of times pu was selected in MARXAN when optimized for ecological costs X03 = incl.OS. number of times pu was selected in MARXAN when optimized for social costs X04 = incl.OS. ecological costs (ECUess) o