微电网
汽车工程
调度(生产过程)
峰值负荷
随机性
调峰发电厂
峰值需求
电动汽车
荷电状态
蒙特卡罗方法
工程类
计算机科学
功率(物理)
模拟
电气工程
电
分布式发电
电压
电池(电)
可再生能源
量子力学
物理
统计
数学
运营管理
作者
Kaile Zhou,Lexin Cheng,Lulu Wen,Xinhui Lu,Tao Ding
出处
期刊:Energy
[Elsevier]
日期:2020-12-01
卷期号:213: 118882-118882
被引量:65
标识
DOI:10.1016/j.energy.2020.118882
摘要
The uncoordinated charging of large amounts of electric vehicles (EVs) can lead to a substantial surge of peak loads, which will further influence the operation of power system. Therefore, this study proposed a coordinated charging scheduling method for EVs in microgrid to shift load demand from peak period to valley period. In the proposed method, the charging mode of EVs was selected based on a charging urgency indicator, which can reflect different charging demand. Then, a coordinated charging scheduling optimization model was established to minimize the overall peak-valley load difference. Various constraints were considered for slow-charging EVs, fast-charging EVs, and microgrid operation. Furthermore, Monte Carlo Simulation (MCS) was used to simulate the randomness of EVs. The results have shed light on both the charging modes selection for EV owners and peak shaving and valley filling for microgrid operation. As a result, this model can support more friendly power supply-demand interaction to accommodate the increasing penetration of EVs and the rapid development of flexible microgrid.
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