A coordinated charging scheduling method for electric vehicles considering different charging demands

被引：110
作者：
Zhou, Kaile [1 ,2 ,3 ,4 ]
Cheng, Lexin [1 ,2 ]
Wen, Lulu [1 ,2 ]
Lu, Xinhui [1 ,2 ,3 ,4 ]
Ding, Tao [1 ,2 ,3 ,4 ]
机构：
[1] Hefei Univ Technol, Sch Management, Hefei 230009, Peoples R China
[2] Hefei Univ Technol, Minist Educ, Key Lab Proc Optimizat & Intelligent Decis Making, Hefei 230009, Peoples R China
[3] Hefei Univ Technol, Intelligent Interconnected Syst Lab Anhui Prov, Hefei 230009, Peoples R China
[4] Minist Educ, Engn Res Ctr Intelligent Decis Making & Informat, Hefei 230009, Peoples R China
来源：
ENERGY | 2020年 / 213卷
基金：
中国国家自然科学基金;
关键词：
Electric vehicles; Coordinated charging; Optimal load scheduling; Charging demand;
D O I：
10.1016/j.energy.2020.118882
中图分类号：
O414.1 [热力学];
学科分类号：
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. (c) 2020 Elsevier Ltd. All rights reserved.
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页数：13
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