Modeling and Simulation
Vol.3 No.04(2014), Article ID:14324,8 pages
DOI:10.12677/MOS.2014.34012

The Prediction of Electric Vehicles Charging Load Based on Monte Carlo Simulation

Huan Pan, Wenjuan Qiao, Nan Li

School of Physics Electrical Information Engineering and Ningxia Key Laboratory of Intelligent Sensing for Desert Information, Ningxia University, Yinchuan

Email: 249540592@qq.com, ph0303@126.com

Received: Sep. 17th, 2014; revised: Oct. 20th, 2014; accepted: Oct. 27th, 2014

ABSTRACT

The charging load of a large number of electric vehicles is predicted in this paper. Based on the trends of electric vehicles in China, the electric vehicles are divided into electric buses, electric taxis, electric officer’s car and electric private car according to different use. The charging mode and time of different kinds of electric vehicles are discussed. The Monte Carlo simulation method is applied to determine the starting state of charge (SOC) and the initial charging point. The charging loads of four kinds of electric vehicles are calculated. The corresponding four charging curves and the total curves are obtained via simulation. Through analyzing the character of the curves, the influence factors of electric vehicles charging load in future are summarized and the suggestion for charging equipment building is provided.

Keywords:Electric Vehicles, Monte Carlo Simulation, Charging Load, Charging Mode

1. 引言

2. 不同车辆运营及充电特性分析

2.1. 公交车

2.2. 出租车

2.3. 公务车

2.4. 私家车

3. 不同车辆运营及充电特性分析

3.1. 电动汽车充电负荷计算模型

(1)

3.2. 基于蒙特卡洛的电动汽车充电负荷计算方法

4. 电动汽车充电负荷曲线预测

4.1. 各种类型电动汽车保有量预测

4.2. 参数设置

4.3. 电动汽车充电负荷曲线

Figure 1. The flowchart of electric vehicles charging based on Monte Carlo simulation

Table 1. The predicted results of the number of electric vehicles in China

Table 2. The analysis of charging character of electric vehicles

(a)(b)(c)

Figure 2. Load curves of all kinds of electric vehicles: (a) Electric buses in 2015; (b) Electric taxies in 2015; (c) Electric officer’s cars in 2015; (d) Electric private cars in working day in 2015; (e) Electric private cars in rest day in 2015

Visual C++ 6.0环境下运行程序，将图2中的4种类型电动汽车充电负荷进行叠加，可以分别得到2015年工作日与节假日时的总充电负荷曲线，如图3图4所示。应用相同的方法，可分别得到2020、2030年工作日与休息日的中国电动汽车充电负荷曲线，如图5图6所示。

4.4. 结果分析

(1) 2015年工作日充电负荷峰值为709.06 MW，节假日充电负荷峰值为357.49 MW；2020年工作日充电负荷峰值为2537.07 MW，节假日充电负荷峰值为6321.82 MW。

(2) 2015~2030年，随着电动汽车的逐渐普及，4种类型的电动汽车充电负荷呈现快速上升趋势。

(3) 电动私家车将是今后发展的主流，因此未来电动汽车的主要充电负荷来自电动私家车。

(4) 电动汽车充电的负荷高峰期主要集中在下班后至晚上10点左右，产生这个高峰的主要原因是大

Figure 3. Load curves in working day in 2015

Figure 4. Load curves in rest day in 2015

Figure 5. Load curves in working day in 2020 and 2030

Figure 6. Load curves in rest day in 2020 and 2030

5. 结论

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