Multi-level distributed demand response study for a multi-park integrated energy system

Abstract

Current studies of integrated demand response (IDR) across multiple campuses often use centralized, unified scheduling with individual campuses as the object of analysis, which ignores the independent autonomy of users within the park. To this end, this paper proposes a multi-level distributed demand response model for a multi-park integrated energy system, which is solved using a combination of the particle swarm optimization algorithm and mixed integer linear programming software. First, based on the existing two-part tariff, an energy management system is introduced to construct a park integrated demand response market based on a noncooperative game. Second, load aggregators are used as a link to form an optimized alliance of multiple parks, and the overall economy of the coalition is optimized through a cooperative game of multiple parks. The model allows for coordination and complementarity based on zonal autonomy, maximizing economic efficiency and exploring the demand response capability of users. Finally, an arithmetic simulation is carried out with a scenario of a day-ahead electricity peaking auxiliary service market, and the results verify the feasibility and economics of the designed model in a scenario where multiple parks participate in integrated demand response.