Day-ahead Optimal Price Strategy of Virtual Power Plant to Coordinate Multi Integrated Energy Systems Dispatched by EFIS

The current trend is to achieve regionalized energy control through an integrated energy system and utilize virtual power plants for power regulation support. This paper proposes a day-ahead optimal price strategy of virtual power plant to coordinate multi integrated energy systems dispatched by evolution fuzzy inference system. The mathematical model of the integrated energy system and virtual power plant is first established, followed by an analysis of the scheduling using evolutionary fuzzy inference system and the feasibility of obtaining real-time electricity prices through a master-slave game. Finally, the proposed solution is evaluated through simulation experiments, resulting in an 8.4% optimization of economic indices for the integrated energy system and enabling peak cutting and valley filling. These results confirm its effectiveness and economic benefits.