A Conceptual Model of a Multi-Agent System to Simulate Collective Behaviors in Renewable Energy Communities

The urgent need for a global energy transition towards sustainability has underscored the importance of Renewable Energy Communities (RECs) in promoting local green energy production and consumption. Managing these communities is complex due to the diverse behaviors of members influenced by various factors. This paper proposes a conceptual model of a multi-agent system that integrates the Theory of Planned Behavior and Activity Theory to simulate individual and collective behaviors within energy communities. By leveraging the psychological insights of the Theory of Planned Behavior and the socio cultural perspective of Activity Theory, the conceptual model aims to enhance the understanding of behavioral dynamics within RECs, thereby informing management strategies and energy policies. The model is designed to simulate energy behaviors and interactions between agents and their environment. Agents, representing consumers and producers, make decisions based on attitudes, subjective norms, and perceived behavioral control as outlined by the Theory of Planned Behavior. The system’s environment, structured by Activity Theory, organizes agents’ interactions and incorporates tools, roles, rules, and norms governing the activities within energy communities. Future simulations under various scenarios will allow the evaluation of management strategies, facilitating the transition towards sustainable energy practices. This socio-technical approach offers a detailed framework for modeling energy community behaviors and demonstrates the efficacy of multi-agent systems in studying complex energy systems.