Community-Oriented Energy Trading Strategy in Multiagent Cloud Energy Storage Framework

Cloud energy storage (CES) is a cost-effective solution for residential energy sharing, transforming consumers into self-sufficient ones. This paper uses a multiround seller–buyer matching strategy to introduce an optimized energy management model for end-to-end (E2E) energy trading. The seller–buyer offers the bid multiple times in a time slot. The model considers factors, such as agent load profile, distributed energy resources, user grid cost, energy trading cost investment for individual batteries, and CES. The efficacy of the proposed model is substantiated through simulation. The main highlights are introducing a single-round seller–buyer matching strategy and a multiround seller–buyer matching strategy to determine the market clearing price for E2E energy trading between agents. Simulations show that CES user agents reduce costs, reduce grid energy demand, and increase profit for users, with overall community costs reduced by 36.05% and profit increased by 17.10% with a single-round seller–buyer matching strategy. The proposed trading strategy has also been validated using market data from India and British Columbia, Canada.