Research on resource aggregation scheduling and optimization control strategy of virtual power plant based on spatio-temporal data mining computational analysis

In recent years, virtual power plants have rapidly emerged as a flexible and efficient form of intelligent energy management.This paper focuses on the optimal scheduling of virtual power plant resources, after explaining the virtual power plant resources and their characteristics, it proposes a new energy consumption model of virtual power plant with hybrid energy storage system, establishes a joint optimal scheduling model of thermoelectricity and electricity based on the hybrid storage system, and selects the improved particle swarm algorithm for the optimization and solving.Collecting the relevant spatio-temporal data of the system power generation for example analysis, the improved particle swarm algorithm has better convergence, and the optimal allocation of energy storage is realized when the electric energy storage and thermal energy storage are 9MWh and 35MWh, respectively, and then the annual profit of the virtual power plant can be increased by 605,610,000 yuan.In addition, after the aggregated scheduling of the model, the electric load demand response and the electric energy storage work together to maintain the balance of the electric output of the virtual power plant.The proposed optimization control strategy can realize the complementary advantages of distributed resources, improve the flexible regulation ability of the virtual power plant, alleviate the pressure of power supply preservation, and ensure the safe and smooth operation of the power grid.