Research on energy management of multi-charging station

Electric vehicle charging station can coordinate the scheduling of photovoltaic power generation units, lithium battery energy storage units, and electric vehicle charging loads to improve the utilization rate of renewable energy. This paper takes the group of optical storage stations as the research object, and based on historical data, the photovoltaic power prediction based on random forest and the load power prediction of electric vehicles based on BP neural network are realized. At the same time, this paper establishes a static energy management model, determines the objective function and budget conditions, studies the energy transactions between optical storage stations, and substitutes the predicted data into the energy management model. The linear programming algorithm is used to optimize the load index of each charging station, reduce the operating cost and improve the economy. Based on the historical data of three optical charging stations, simulation analysis shows that the energy management strategy proposed in this paper can effectively optimize the load index of each optical charging station and improve economic benefits.