Multi-Agent Simulator for Evaluating the Social and Economic Dynamics of Renewable Energy Communities with NetLogo: A Decision Support System tool for the evaluation of RECs

The transition toward a decentralized and decarbonized energy paradigm finds a pivotal instrument in Renewable Energy Communities (RECs). However, their operational dissemination is often hindered by the structural limitations of current planning tools, which are typically confined to a purely techno-economic approach that treats the end-user as a perfectly rational actor, ignoring their behavioral complexity. This thesis presents the development, validation, and empirical application of an innovative holistic Decision Support System (DSS), based on an Agent-Based Model (ABM) implemented in the NetLogo environment. The proposed computational framework overcomes technological reductionism by simultaneously integrating three levels of analysis: thermodynamic, economic-regulatory, and, in an entirely unprecedented way, psychosocial. Through the mathematical formalization of Serge Moscovici’s Active Minority Theory, the simulator succeeds in quantifying social influence, trust dynamics, and the attrition rate (Churn Rate) in response to operational fluctuations. Following a rigorous empirical testing process, the model was applied to real datasets from three pioneering initiatives in Sardinia (Cagliari, Calasetta, and Simala). The investigation focused on a scenario analysis of the urban REC in Cagliari, located in a Public Residential Housing (ERP) neighborhood with high socio-economic vulnerability. The virtual community was subjected to a stress-test matrix crossing the Italian (Feed-in Premium) and Spanish (Net Billing) regulatory frameworks with sudden stochastic energy price shocks. The computational results unequivocally demonstrate that engineering efficiency alone is insufficient to guarantee project survival. The simulations reveal the existence of a rigid demographic "Carrying Capacity," the marked inefficacy of the pure Net Billing model in combating energy poverty in the absence of storage systems, and the dramatic asymmetry of social capital—capable of being built over years of painstaking persuasion but ready to disintegrate instantaneously when economic benefits fail (The Great Churn). The work concludes that to ensure the long-term success of decentralized energy infrastructures, public decision-makers must adopt controlled sizing logics and "adaptive welfare" statutory policies. The tool delivered to the scientific community and public administrations thus configures itself as a powerful in silico laboratory, essential for simulating and governing human complexity even before technological complexity, guiding territories toward an ecological transition that is authentically just, resilient, and inclusive.