Assessment of photovoltaic energy potential over Italy from an ensemble of convection permitting climate models
Year: 2026
Type: article
Abstract: Photovoltaic (PV) energy production is crucial to achieve climate neutrality by 2050 and is tightly linked to climate variability and change. In particular, variations in the availability of surface solar radiation impact PV energy potential, while temperature and wind affect PV cell efficiency. Here, for the first time, we evaluate the ability of a 16-member km-scale convection-permitting climate model (CPMs) ensemble to reproduce PV energy potential over Italy. The assessment is conducted at station and national level using ERA5-land reanalysis dataset as reference. Driving climate variables are further evaluated against available high-resolution observations. The quality assessment of CPMs and ERA5-land data reveal an overestimation of downward shortwave radiation at the surface by CPMs (+6% in summer) and underestimation by similar amounts in ERA5-land compared to the high-resolution observational dataset. The 2m temperatures and 10 m wind speeds are slightly overestimated in CPMs as well by 1.24C and 0.54 m/s respectively. Based on this good agreement, the energy potential model previously validated with ERA5-land is applied to CPMs. The CPM ensemble shows realistic diurnal and seasonal cycles, but tends to overestimate PV potential relative to ERA5-land by up to +10 % at individual stations and +13 % at bidding zones, in particular due to the bias in radiation. Ensemble spread is 20% in summer, but significantly lower within model families. These findings support the use of CPM ensembles for climate change impact studies on solar resources, providing high resolution information to support adaptation strategies in power system planning at local scale.
Source: Renewable Energy
Authors: Milan Mathew, Giorgia Fosser, Marco Gaetani, Anna Malagò, Alberto Ravasi, Andreas Will, Eleni Katragkou, Stergios Kartsios, Marianna Adinolfi, Ozan Mert Göktürk, Hylke de Vries, Rita M. Cardoso, Pedro M.M. Soares, Andreas Dobler, Sophie Bastin, Merja H. Tölle, Klaus Goergen, Pierre Nabat, Heimo Truhetz, Luna Santina Lehmann
Institutions: Istituto Universitario di Studi Superiori di Pavia, Brandenburg University of Technology Cottbus-Senftenberg, Aristotle University of Thessaloniki, CMCC Foundation - Euro-Mediterranean Center on Climate Change, Bjerknes Centre for Climate Research, NORCE Research AS, University of Lisbon, Instituto Dom Luiz, Norwegian Meteorological Institute, Centre National de la Recherche Scientifique, Université de Versailles Saint-Quentin-en-Yvelines, Université Paris-Saclay, Sorbonne Université, Institut Pierre-Simon Laplace, Laboratoire atmosphères, milieux, observations spatiales, University of Kassel, Türkisch-Deutsche Universität, Forschungszentrum Jülich, Centre National de Recherches Météorologiques, Météo-France, University of Graz, ETH Zurich, Institute for Atmospheric and Climate Science
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,460
OpenAlex ID: W7213506857