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A charging pricing strategy of electric vehicle fast charging stations for the voltage control of electricity distribution networks

Dong, Xiaohong, Mu, Yunfei, Xu, Xiandong, Jia, Hongjie, Wu, Jianzhong, Yu, Xiaodan and Qi, Yan 2018. A charging pricing strategy of electric vehicle fast charging stations for the voltage control of electricity distribution networks. Applied Energy 225 , pp. 857-868. 10.1016/j.apenergy.2018.05.042
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Abstract

With the increasing number of electric vehicles (EVs), the EV fast charging load will significantly affect the voltage quality of electricity distribution networks. On the other hand, EVs have potentials to change the choices of charging locations due to the incentives from the variations of charging prices, which can be considered as a flexible response resource for electricity distribution networks. In this paper, a charging pricing strategy of EV fast charging stations (FCSs) was developed to determine the pricing scheme for the voltage control of electricity distribution networks, which consisted of a simulation model of EV mobility and a double-layer optimization model. Considering the travel characteristics of users, the simulation model of EV mobility was developed to accurately determine the fast charging demand. Taking the total income of FCSs and the users’ response to the pricing scheme into account, the double-layer optimization model was developed to optimize the charging pricing scheme and minimize the total voltage magnitude deviation of distribution networks. A test case was used to verify the proposed strategy. The results show that the spatial distribution of EV fast charging loads was reallocated by the proposed charging pricing scheme. It can also be seen that the proposed strategy can make full use of the response capacity from EVs to improve the voltage profiles without decreasing the income of the FCSs.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 0306-2619
Date of First Compliant Deposit: 1 August 2018
Date of Acceptance: 7 May 2018
Last Modified: 29 May 2019 23:38
URI: http://orca.cf.ac.uk/id/eprint/113605

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