Integrated configuration and charging optimization of aggregated electric vehicles with renewable energy sources

被引:6
|
作者
Gao, Shuang [1 ]
Jia, Hongjie [1 ]
Liu, Jiahao [1 ]
Liu, Chunhua [2 ]
机构
[1] Tianjin Univ, Sch Elect & Informat Engn, Tianjin, Peoples R China
[2] City Univ Hong Kong, Sch Energy & Environm, Hong Kong, Peoples R China
来源
INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS | 2019年 / 158卷
基金
国家重点研发计划;
关键词
electric vehicle aggregator; optimal configuration and operation; power quality; charging infrasturcture; ANCILLARY SERVICES; SYSTEMS;
D O I
10.1016/j.egypro.2019.01.968
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The commercialization and wide application of electric vehicles (EVs) rely on the development of EV charging infrastructure and its coordinated operation in the electric power grid with renewable energy sources. As the EV aggregator is introduced as intermediate control entity to form a multi-layer control framework, the optimal configuration of EV aggregator and the charging power regulation are closely related to each other. This paper proposes an integrated optimization to solve the mixed configuration and operation problem of EV aggregator. A hybrid optimization algorithm based on partial swarm optimization (PSO) and sequential quadratic programming (SQP) is formulated to find the best solution for the location and size of EV aggregator in the distribution network and the charging scheduling of each individual EV. The master problem in the coupled optimization algorithm is to calculate the optimal configuration of the EV aggregator based on the estimation of the EV charging load, and based on the setting of EV aggregator the subproblem is to obtain the charging plan for individual EV under the day ahead optimal dispatching of charging demand in the distribution grid. Finally, 123-bus distribution system is adopted to analyze the characteristics of the proposed model for concurrent optimization of EV aggregator and its operation in the test distribution network. The simulation results validate the hybrid optimization algorithm in integrated configuration and operation of EV charging infrastructure. (C) 2019 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:2986 / 2993
页数:8
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