基于粒子群算法的电动汽车电能计量优化

An electric vehicle energy metering optimization based on particle swarm optimization

电动汽车充电过程中电能的准确计量对其推广具有重要研究意义。该文建立了三相电压不平衡度模型,以三相电压不平衡度最小为优化目标,利用标准粒子群(Particle Swarm Optimization,PSO)算法采用MATLAB编程对其进行优化,根据优化结果通过调整单相电价的方式引导电动汽车有序充电,使得三相电压不平衡度最小。最终解决电动汽车充电过程中由于负荷不平衡引起的三相电压不平衡导致单相充电用户收费不合理的问题。算例分析表明,标准粒子群算法能够有效地优化电动汽车作为单相负荷引起的三相电压不平衡问题。

The accurate measurement of electric energy in the process of charging of electric vehicles is great significance to its promotion.The three-phase voltage unbalance model was established,and the optimization objective was to minimize the three-phase voltage unbalance.The standard particle swarm optimization(PSO)algorithm was applied to optimize the three-phase voltage unbalance model with MATLAB programming.According to the optimization results,the orderly charging of electric vehicles is guided by adjusting the single-phase electricity price,make the three-phase voltage imbalance is minimized.Finally,the charge unreasonable problem of single-phase users of three-phase voltage unbalance caused by load unbalance in the charging process of electric vehicle is solved.Example analysis shows that the particle swarm optimization can effectively optimize the three-phase voltage unbalance problem caused by the single-phase load of electric vehicles.