Economic Optimization Model of Building Aggregator Based on Multi-Agent Master-Slave Game

In the future electricity market environment, to achieve economic optimization scheduling for building entities with different interests, this paper proposes a building economic optimization model based on price-based demand response and a leader-follower game. The model aims to maximize the economic benefits of load aggregators, minimize the electricity costs for electric vehicles and air conditioners, and maximize the economic benefits of distributed power source operators. By optimizing the electricity price information released by load aggregators, adjusting the electricity usage strategies of electric vehicles and air conditioners within the building, and changing the electricity selling strategies of building distributed power source operators, a Nash equilibrium is achieved. Simulations have verified that the proposed model can effectively reduce the peak-to-valley difference in building loads and improve the utilization rate of renewable energy in buildings while optimizing the economic efficiency of various building entities.