Virtual Power Plant Optimization Technology with Metro Vehicle Networking (CICED 2024)

With the increasing scale of electric vehicles, the randomness and fluctuation of their power pose a challenge to the stable operation of the power grid. In order to realize the effective aggregation and flexible invocation of various resources, this paper constructs a virtual power plant system model including distributed photovoltaic, wind power, gas turbine, energy storage and electric vehicle. Based on this, a virtual power plant output plan is developed and the maximum output of electric vehicles is constrained by penetration ratio. In order to maximize the economic benefit, the optimal operation model of virtual power plant with metro vehicle network was constructed, and the improved particle swarm optimization algorithm combining Circle mapping and elite reverse learning was used to solve the problem. The effectiveness of the proposed method is verified by an example analysis.