考虑电动汽车时空分布的充电负荷建模

Modeling of charging loads considering the temporal and spatial distributions of electric vehicles

针对电动汽车(electricvehicle,EV)时空转移和充电行为方式具有不确定性的问题,提出一种基于出行链随机模拟EV充电负荷时空分布的方法。首先,根据家用汽车出行调查数据将充电区域划分为6类,借助出行链概念建立EV用户一天行驶的时空分布特征量和状态量,并采用马尔可夫过程模拟EV的空间转移特性;其次,考虑分时电价对充电负荷分布的影响,建立EV车载重量和环境温度的能耗模型;最后,采用蒙特卡洛模拟法对不同类型EV在不同车载重量和温度下、在各充电区域内的充电负荷进行仿真。计算结果表明,所构建的模型可以较准确模拟EV在不同时空分布下的充电需求,在不同充电区域充电负荷具有明显差异,分时电价、环境温度对充电负荷分布具有明显影响,EV载客和环境温度降低时充电负荷呈增加趋势。

To address the uncertainty of temporal and spatial transfer and charging behavior of electric vehicles (EVs), a trip chain based temporal and spatial distribution method is presented for simulating EV charging loads. Firstly, employing the trip chain concept, the feature quantities and state quantities of the temporal and spatial distribution in the daily traveling of EVs are presented. Based on the household travel survey data, a charging area is divided into six categories. The Markov process is used to simulate the space transfer characteristics of EVs. Secondly, considering the impacts of time-of-use electricity price on the distribution of charging loads, the EV energy consumption model is established involving EV weights and ambient temperature. Finally, the well-established Monte Carlo simulation method is used to examine various scenarios, including different types of EVs with different vehicle weights and under various temperatures.The charging loads in each charging area can be attained. Simulation results show that the presented model can accurately simulate charging demands of EVs under various temporal and spatial distributions. In different charging areas charging loads exhibit different characteristics. The time-of-use electricity price and ambient temperature have significant impacts on EV charging load distributions. Increasing weights of EVs and decreasing ambient temperature could result in charging loads go up.