Daily Dispatching Optimization Model of Virtual Power Plant with Integrated Energy Buildings

Abstract

In order to make rational use of resources to improve the terminal energy utilization rate and improve the reliability of day ahead optimization, this paper studies the optimal dispatching potential of virtual power plant with integrated energy buildings considering the uncertain factors such as load forecasting error. Taking into consideration the system security constraints, the day ahead optimal scheduling model of the virtual power plant with comprehensive energy buildings is established to minimize the economic costs including operation and depreciation costs and is solved combining the strategy of dynamically adjusting inertia weights based on S- curve with particle swarm optimization and differential hybrid algorithm. We then analyze the simulation results of buildingtype virtual power plant in summer and winter scenarios, which verify the effectiveness of the improved algorithm.