A scalable game-theoretic framework for secure and decentralized energy sharing in renewable energy communities

Abstract

This paper presents a secure distributed method for optimizing the operation of Renewable Energy Communities (RECs), aligning individual member benefits with collective sustainability goals. The proposed framework utilizes game theory to reach an equilibrium between users’ decisions and Paillier homomorphic encryption to enable privacy-preserving collaboration among community members without relying on a central authority. By aggregating the results of distributed optimizers operating at user premises, members can select strategies that maximize their individual benefits. The aggregation of players’ strategies results in a collective self-consumption behavior accompanied by rewards, and these collective actions of participants are adjusted in subsequent rounds of the game based on the strategies of others to achieve an optimal outcome. The distributed nature of this method spreads the computational workload across all users, making it suitable for implementation on low-cost devices. Thus, the method is scalable, device-agnostic, and suitable for low-cost hardware. Evaluations on different community scenarios demonstrate effective convergence to optimal energy sharing with minimal reliance on energy storage systems, confirming the method’s practical viability and robustness under varying users’ profiles and configurations.