Stochastic Collaborative Planning Method for Electric Vehicle Charging Stations

被引：0
|
作者：
Wang, Shu [1 ]
Meng, Ke [1 ]
Luo, Fengji [2 ]
Xu, Zhao [3 ]
zheng, Yu [4 ]
机构：
[1] Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW, Australia
[2] Univ Sydney, Sch Civil Engn, Sydney, NSW, Australia
[3] Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
[4] CSG, Elect Power Res Inst, Guangzhou 510080, Guangdong, Peoples R China
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON SMART GRID COMMUNICATIONS (SMARTGRIDCOMM) | 2016年
关键词：
Electric vehicle; charging station; multi-objective optimization; distribution system planning; vehicle-to-grid;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Electric vehicles (EV) is a promising solution for reducing the environment adverse effect of road transport. In this study, a multi-objective, multi-stage collaborative planning model is proposed for the integrated EV charging stations and power distribution network. The proposed model aims to minimize the investment & operation costs of the distribution system and maximize the annually captured traffic flow. The uncertainties for both slow charging load and fast charging load are considered. The MOEA/D algorithm is employed to find the Pareto frontier of the proposed model. Simulations based on a case study of a 54-node distribution system and a 25-node traffic network system proves the effectiveness of proposed method.
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页数：6
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