Volume 19, Issue 1 (JIAEEE Vol.19 No.1 2022)
Journal of Iranian Association of Electrical and Electronics Engineers 2022, 19(1): 319-329 |
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Azad M, Ghayeni M. Optimal placement of fast charging stations for electric vehicles with consideration of exchange between regions using genetic algorithm - Case study for Mashhad. Journal of Iranian Association of Electrical and Electronics Engineers 2022; 19 (1) :319-329
URL: http://jiaeee.com/article-1-695-en.html
URL: http://jiaeee.com/article-1-695-en.html
Department of Electrical Engineering, Sadjad University of Technology, Mashhad
Abstract: (1601 Views)
In this paper, a new method for locating fast electric charging stations with a regional perspective and taking into account the coefficient of interchange between regions is proposed. First, the city must be divided into specific areas, then, using the parameters of electric vehicle density, the required earth and social visibility of the region, the initial candidate points in each area are determined. Given land price and distance from the network substation as the main parameters, the location of the construction of the fast charging station is defined as an optimization problem and then solved by the genetic algorithm. In the proposed method, in addition to the location of the fast charging stations, the number of fast charging units (capacities) at each station is also determined. In the proposed algorithm, by defining the coefficient of exchange between adjacent regions, it is possible to relocate charging units so that the number of charge units can be flexible in proportion to the price of land in each area. The proposed method has been implemented for Mashhad metropolitan area with consideration of nine areas in accordance with the Mashhad power distribution company and the results of simulation for different scenarios are presented.
Keywords: Electric vehicle, fast charging station, placement, zonal perspective, coefficient of exchange, genetic algorithm
Type of Article: Research |
Subject:
Power
Received: 2018/10/22 | Accepted: 2019/01/27 | Published: 2022/04/14
Received: 2018/10/22 | Accepted: 2019/01/27 | Published: 2022/04/14
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