Multi-objective optimal scheduling of wind-photoelectric-storage virtual power plants considering demand response

Abstract

In this paper, a multi-objective optimal scheduling model of wind-photovoltaic storage virtual power plant with demand response is established. Under system constraints, an economical and environmentally friendly virtual power plant integrated optimization scheduling model was proposed to minimize the total cost of virtual power plant and maximize the utilization rate of wind power and photovoltaic. At the same time, this paper improves MOPSO optimization algorithm, and uses nonlinear exponential decline function to obtain the algorithm inertia, which effectively improves the algorithm convergence performance and the distribution characteristics of pareto frontier. The simulation results show that the model can guide the multi-objective optimal scheduling of virtual power plant to a certain extent.