Cooperative-Game-Based Day-Ahead Scheduling of Local Integrated Energy Systems With Shared Energy Storage

Abstract

In the context of the current sharing economy, the application of shared energy storage (SES) among local integrated energy systems (LIESs) is underexplored. There is an urgent need for developing appropriate modeling and solution methods so as to facilitate the application of SES among LIESs. To this end, this paper proposes a cooperative-game-based day-ahead scheduling model of LIESs with SES. The proposed model can be transformed into a sequential two-step optimization problem for alleviating the computational complexity. More specifically, the subproblem of cooperative alliance profit maximization is established in the first step to obtain the optimal scheduling strategies of each LIES, while the subproblem of SES bargaining is constructed in the second step to obtain the optimal pricing information. Besides, a distributed solution algorithm based on the alternating direction method of multipliers with a warm start and dual update accelerated iteration strategies (ADMM-W-D) is proposed to effectively preserve the privacy of each LIES and improve the convergence performance of traditional ADMM. Case studies show that the proposed model can achieve lower operating costs and higher renewable energy consumption levels of LIESs after considering SES. It is also demonstrated that the proposed algorithm based on ADMM-W-D has stronger convergence and better scalability than traditional algorithms.