Economic evaluation of customer side energy storage based on hybrid leapfrog particle swarm optimization algorithm

Customer side energy storage has the benefits of cutting peak and filling valley, reducing line loss, etc. This paper conducts economic research on customer side energy storage and studies the realization value of its optimal configuration. First of all, considering the benefits of reducing substation capacity and power purchase cost due to energy storage on the customer side, combined with battery investment and operation and maintenance costs, a benefit cost model is built. Secondly, the leapfrog algorithm is introduced into the traditional particle swarm optimization algorithm, and the battery constraint function is used to achieve the maximum optimization. Finally, the hybrid leapfrog particle swarm optimization algorithm is used to solve the example. The results show that the customer side energy storage has the realization economy, and the configuration optimization can be realized by using the hybrid leapfrog particle swarm optimization algorithm. The paper can provide theoretical reference for operational decision-making.