Robust model of electric vehicle charging station location considering renewable energy and storage equipment

被引:114
作者
Li, Chengzhe [1 ,2 ]
Zhang, Libo [1 ,2 ]
Ou, Zihan [1 ]
Wang, Qunwei [1 ,2 ]
Zhou, Dequn [1 ,2 ]
Ma, Jiayu [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Econ & Management, Nanjing 211106, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Res Ctr Soft Energy Sci, Nanjing 211106, Peoples R China
基金
中国国家自然科学基金;
关键词
Electric vehicle charging stations; Location; Renewable energy; Energy storage systems; Robust optimization; NETWORK; SYSTEM; WIND; COORDINATION; EQUILIBRIUM; GENERATION; OPERATION;
D O I
10.1016/j.energy.2021.121713
中图分类号
O414.1 [热力学];
学科分类号
摘要
The location of electric vehicle charging station (EVCS) is one of the critical problems that restricts the popularization of electric vehicle (EV), and the combination of EVCS and distributed renewable energy can stabilize the fluctuation of renewable energy output. This article takes a micro-grid composed of the power distribution such as wind power and photovoltaic (PV), EVCSs and energy storage systems (ESS) as the research object. The uncertainties of EVs' charging demand and distributed renewable energy output are considered. A robust optimization model for the location of charging stations with distributed energy is proposed based on the combination of the road network and the grid. Load fluctuation rate is used to evaluate the degree of fit between the renewable energy uncertain output curve and the charging de-mand curve to determine the appropriate capacity of the wind and PV generation system and ESS. The method of kernel density estimation is used to improve the issue of over-conservatism of the robust optimization. Finally, a simulation is carried out on a network which consists of an IEEE 33-node power distribution network and a 25-node transportation system. The robustness and economy of the model are demonstrated by the results of simulation given. (c) 2021 Elsevier Ltd. All rights reserved.
引用
收藏
页数:14
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