A Secure and Distributed Method for Energy Communities' optimal operation

Abstract

In this paper, we represent a secure distributed method to allow collaboration between the users of an energy community while guaranteeing their privacy. By aggregation of distributed optimizers in users' property, members are enabled to choose their strategies to maximize their own benefit. The summation of players' strategies leads to a collective consumption behavior with associated reward and these collective actions of members are modified during consecutive rounds of a game depending on the others' strategies to reach the optimum point. The distributed scheme of this method splits the computational burden among all users and makes it appropriate to be implemented on low-cost devices. Furthermore, the proposed method gives the opportunity to the users to have their preferences beside the energy community's global objective. The assessment of the method on a 10-user Energy Community proves that after few rounds of the game, users reach an optimum equilibrium point that not only maximizes each users benefit, but also meets the community target.