The progress of technology promotes the energy storage power station to play an increasingly important role in the energy system. In this paper, a multi-objective cooperative control strategy based on improved differential evolutionary algorithm is proposed for the optimization of power conversion system (PCS) equipment of lithium iron phosphate battery energy storage power station. An operation model considering the dynamic energy efficiency characteristics of the battery is constructed, and the optimal operation strategy is converted into an objective function solving problem. The differential evolutionary algorithm is introduced and combined with adaptive parameter adjustment and hybrid mutation strategy to optimize the power allocation and charging/discharging scheduling of the PCS equipment. It is shown that the improved differential evolutionary algorithm can effectively regulate the PCS equipment under the influence of two power steps: 0.9 MW output and 15 MW of discharge and 15 MW of charge, and the algorithm can still stably output effective optimization strategies under the two extreme conditions of SOC close to the extremes of 0.75 and 0.85. Comparison of the four objective evaluation indexes shows that the improved differential evolutionary algorithm has better performance than the other algorithms.
