Enhancing the impact of energy system modeling on regional policy: a case study of knowledge exchange in Piemonte Region, Italy

Abstract Energy system modeling has become a critical tool for guiding energy transition plans at different administrative levels, yet a persistent gap exists between modeling outputs and practical policy implementation. This paper presents a novel co-creation approach applied for the Piemonte Region, Italy, that successfully bridges this divide through structured knowledge exchange between researchers and public officers. Using the EPLANopt model—which combines multi-objective evolutionary algorithms with EnergyPLAN simulation software—we developed optimized deep decarbonization scenarios for the regional energy system for 2030, 2040, and 2050. The modeling framework integrated all major energy sectors (electricity, heating, transportation, and industry) while comprehensively evaluating various renewable technologies, including different photovoltaic (PV) configurations, wind power, hydrogen production, energy storage systems, and efficiency measures. Through geographic information systems-based spatial analysis, we identified and quantified the technical potential of renewable energy sources across the region, incorporating territorial constraints and environmental considerations. The participatory approach fostered continuous dialogue between modelers and regional authority, resulting in scenarios that better reflect local priorities, constraints, and implementation capacity. Our findings demonstrate that this co-creation methodology leads to more robust and feasible energy transition scenarios, offering targeted recommendations for technology deployment with spatial and temporal specificity. Key actions include expanding rooftop PVs, establishing agrivoltaics regulations, improving energy efficiency in older buildings, investing in storage and flexible energy systems, promoting industrial decarburization, and maximizing local economic benefits through support for regional supply chains.