充电站
电动汽车
光伏系统
需求响应
分类
遗传算法
计算机科学
汽车工程
利润(经济学)
功率(物理)
电气工程
电
工程类
物理
量子力学
机器学习
微观经济学
经济
程序设计语言
作者
Fangzhou Xia,Hongkun Chen,Hao Li,Lei Chen
出处
期刊:Energy Reports
[Elsevier BV]
日期:2022-10-22
卷期号:8: 399-412
被引量:15
标识
DOI:10.1016/j.egyr.2022.10.062
摘要
The charging demand response of electric vehicle(EV) users will affect the social and economic benefits of fast charging services, so it is an important factor in EV charging station planning. In this paper, a photovoltaic-storage fast charging station(PSFCS) planning method considering charging demand response is proposed. Firstly, the EV fast charging behaviors and the factors influencing the admitting ability of PSFCS to the fast charging load are discussed, and the interaction characters between them are analyzed. Based on the above analysis, a three-stage dual-objective optimization model of PSFCS planning considering charging demand response is proposed and solved by the elitist non-dominated sorting genetic algorithm(NSGA-II). Finally, the case study is formulated based on the 21 power nodes-12 traffic nodes network, simulation results show that the proposed method can effectively improve the profit of charging service providers and reduce the total charging time of EVs.
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