Energy storage capacity configuration of electric vehicle charging station with PV under peak shaving mode
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Paper number
1365
Working Group Number
Conference name
CIRED 2019
Conference date
3-6 June 2019
Conference location
Madrid, Spain
Peer-reviewed
Yes
Short title
Convener
Authors
Shi, Shanshan, State Grid Shanghai Electric Power Research Institute, China
Zhang, Yu, State Grid Shanghai Electric Power Research Institute, China
Bao, Hailong, State Grid Shanghai Electric Power Research Institute, China
He, Yang, Shanghai University of Electric Power, China
Wang, Yufei, Shanghai University of Electric Power, China
Zhu, Li, Shanghai University of Electric Power, China
Zhang, Yu, State Grid Shanghai Electric Power Research Institute, China
Bao, Hailong, State Grid Shanghai Electric Power Research Institute, China
He, Yang, Shanghai University of Electric Power, China
Wang, Yufei, Shanghai University of Electric Power, China
Zhu, Li, Shanghai University of Electric Power, China
Abstract
By analyzing the fast charging load and intermittent photovoltaic (PV) output connected to charging station, it combines the PV output power and electric vehicle (EV) charging power as equivalent load power, thus the energy storage system (ESS) capacity is configured according to equivalent load for the purpose of peak-shaving. The daily cost of charging station and the root mean square (RMS) of ESS charge-discharge power are taken as objective functions, the ratio of the upper and lower limit power of equivalent load to average charging power of EV are taken as decision variables respectively, so that an ESS capacity configuration model is established. The objective functions are optimized by NSGA-II algorithm with an improved cross distribution index(CDI), and the individuals of the first non-dominated layer after the final iteration are selected as optimal solution. According to the distribution of target values, the upper and lower limit powers of grid are determined, and the ESS capacity is calculated. The results show that the minimum cost is needed when ESS capacity is only enough to store intermittent residual PV energy. Meanwhile, the improved CDI based on the logistic function can better realize optimal solution of the algorithm and accelerate convergence speed of the solution in the later stage of evolution.
Table of content
Keywords
Publisher
AIM
Date
2019-06-03
Published in
Permanent link to this record
https://cired-repository.org/handle/20.500.12455/385
http://dx.doi.org/10.34890/613
http://dx.doi.org/10.34890/613
ISSN
2032-9644
ISBN
978-2-9602415-0-1