Volume 16, Issue 1 (JIAEEE Vol.16 No.1 2019)                   Journal of Iranian Association of Electrical and Electronics Engineers 2019, 16(1): 21-29 | Back to browse issues page

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Amiri A B, Ghayeni M. Improving Fast Charging Methods Using Genetic Algorithm and Coordination between Chargers in Fast Charging Station of Electric Vehicles in Order to Optimal Utilization of Power Capacity of Station. Journal of Iranian Association of Electrical and Electronics Engineers 2019; 16 (1) :21-29
URL: http://jiaeee.com/article-1-863-en.html
Department of Electrical Engineering, Sadjad University of Technology, Mashhad, Iran
Abstract:   (3780 Views)
Fast charging stations are one of the most important section in smart grids with high penetration of electric vehicles. One of the important issues in fast chargers is choosing the proper method for charging. In this paper, by defining an optimization problem with the objective of reducing the charging time, the optimal charging levels are obtained using a multi-stage current method using a genetic algorithm. Another important parameter in station design is determining the number of charging units to optimize the input power capacity. In this paper, for the first time, a new coordination policy has been proposed in order to increase the number of charging units for a given power capacity and thus reduce the charging time of vehicles. Regarding the change of current during the charging time, it is possible to reduce the chargers for work with less power capacity or at the same capacity, the number of chargers can be increased to reduce the charging time. In this condition, the chargers cannot start to work simultaneously and the proposed coordination between the chargers determine the starting time of chargers. The simulation results in MATLAB environment show that by defining the problem of coordination between the chargers, the number of charging units increases and the waiting time of electric vehicles at station will decreased.
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Type of Article: Research | Subject: Power
Received: 2019/04/28 | Accepted: 2019/04/28 | Published: 2019/04/28

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