电动汽车充电站的概率负荷建模

电动汽车充电站负荷的随机性特征,使相关建立具有通用性负荷模型的研究存在一定的困难,针对三类典型电动汽车充电站,即电池更换站、居民区充电站、公共场所充电站,提出了一种以充电方式、地理位置、出行特征为基础的概率负荷建模方法,通过全面研究充电站负荷建模的影响因素,采用蒙特卡洛模拟与概率统计分析规律相结合的方法综合建立三类典型充电站的概率负荷模型。在此基础上,运用粒子群算法优化得到了填谷效应最优的三类典型充电站的优化配置方案,验证了所建立的概率负荷模型的有效性和实用性。

Probabilistic Load Modeling of Electric Vehicle Charging Stations

The load of electric vehicle (EV) charging stations has some stochastic features that make the study on the general load model difficult. In connection with three EV charging stations including battery swap stations, residential quarters charging stations and public charging stations, a probabilistic load modeling method is proposed based on charging modes, locations and trip characteristics. The probabilistic load models of three kinds of EV charging stations are obtained using Monte Carlo simulation and probability statistics analysis, by analyzing some vital factors of charging station load modeling in general. Moreover, optimized configuration schemes of three typical charging stations with best valley effect are obtained by using particle swarm algorithm optimization, and the validity and practicability of the proposed probabilistic load model are verified.