Master-slave game optimization scheduling of virtual power plant considering electric vehicles

In recent years, the number of electric vehicles (EVs) in the power system has increased dramatically. In order to solve the problem of high system operation costs caused by the uncertainty of new energy power generation, this paper proposes a virtual power plant (VPP) master-slave game optimization scheduling method based on the participation of electric vehicles. First, guide electric vehicle users to participate in power system dispatching by setting reasonable prices. Secondly, in order to deal with the uncertainty at both ends of the source and load, a robust interval optimization method is used to make the system take into account both robustness and economy. Then, the model is transformed into a mixed integer linear programming problem for solution through Karush-Kuhn-Tucker (KKT) conditions, duality theory and the large M method. Finally, the optimal pricing strategy and resource output plan of VPP operators are given through calculation examples. It provides an important idea for VPP to centrally manage the charging and discharging behavior of electric vehicles and reduce system operating costs.