基于PSODE算法的机场充电桩规划研究（英文）

Study on airport charging piles planning based on PSODE algorithm

基于当前机场逐步实行车辆“油改电”的大背景,研究了今后机场充电桩的布局规划问题。建立了以充电桩管理建设费用、电动特种车辆路上运行费用及充电等待费用最小为目标函数的充电桩选址模型,在粒子群算法的基础上引入信息互融机制,提出了差分进化粒子群算法作为模型求解方法,克服了粒子群算法易陷入局部最优和精度低的缺陷,增加了种群多样性及全局寻优能力。最后结合机场实例确定充电桩布局选址的具体方案,证明了模型算法的可行性和有效性。

Based on the background of the current airport’s “oil to electricity”, the issue of future’s layout planning of airport charging piles was studied in this paper. The location model of charging piles was established with the objective of minimizing the management costs of charging piles, running costs of electric special vehicles on the road, and charging waiting costs. The information fusion mechanism was introduced on the basis of particle swarm optimization(PSO) to propose a differential evolution particle swarm optimization algorithm. It overcomes the defect that particle swarm optimization is apt to fall into local optimum and low precision, and increases the diversity and global optimization ability of the population. Finally, take the airport as example, the best plan of the site selection for the charging pile layout is confirmed, and the feasibility and effectiveness of the planning model and algorithm are proved.