Research on Energy Management Optimization of Virtual Power Plant Charging Pile Based on Improved Particle Swarm Optimization

The research on large-scale charging pile virtual power plants is extremely important for promoting the popularization of electric vehicles in our daily lives. It should be noted that applying renewable resources and energy storage technology to the charging facilities of electric vehicles plays a very important role in promoting energy conservation and emission reduction, and achieving dual carbon policies. Accordingly, this article provides a comprehensive analysis of the efficiency of photovoltaic power generation and the state of charge of energy storage; concurrently examines the system structure and energy characteristics. In order to optimize the energy management of large-scale charging pile, an improved particle swarm optimization algorithm considering inertia factor and particle adaptive mutation was proposed. Through the analysis of the calculation results, it is shown that it can optimize the energy management of virtual power plants. The overall electricity consumption characteristics of the park have been significantly improved, leading to a notable reduction in peak power grid consumption.