University of Isfahan Computational Intelligence in Electrical Engineering 2821-0689 16 2 2025 06 22 Planning the Optimal Replacement of Fast Charging Stations for Electric Vehicles in Distribution Networks Considering the Impact of EV User's Behavior Planning the Optimal Replacement of Fast Charging Stations for Electric Vehicles in Distribution Networks Considering the Impact of EV User's Behavior 39 52 29366 10.22108/isee.2025.141183.1684 FA Amin Rafrafi Dept. of Electrical Engineering, University of Shahid Beheshti, Tehran, Iran Alireza Sobbouhi Dept. of Electrical Engineering, University of Shahid Beheshti, Tehran, Iran Abolfazl Pirayesh Neghab Dept. of Electrical Engineering, University of Shahid Beheshti, Tehran, Iran 0000-0003-0935-8693 Journal Article 2024 04 21 The use of electric vehicles (EVs) as an emerging sector in transportation is effective in reducing global warming. In this paper, the optimal replacement of a fast charging station (FCS) considering the impact of EV users’ behavior is investigated. The behavior of users is investigated to reduce the charging demand in EVs due to the long driving distance to reach the station. In this article, the nature of the charging behavior of EV users is considered as a fixed point equation, which is calculated by establishing a relationship between the distance entry rate, and its spatial and temporal penalty. The optimal deployment of fast charging stations is modeled by a non-linear exact optimization problem that will determine the optimal locations for FCS construction. A proposed method based on a genetic algorithm is presented to solve this problem. The simulation results prove the effectiveness of the proposed algorithm in maximizing the profit for the FCS construction company, considering the power grid constraints. The use of electric vehicles (EVs) as an emerging sector in transportation is effective in reducing global warming. In this paper, the optimal replacement of a fast charging station (FCS) considering the impact of EV users’ behavior is investigated. The behavior of users is investigated to reduce the charging demand in EVs due to the long driving distance to reach the station. In this article, the nature of the charging behavior of EV users is considered as a fixed point equation, which is calculated by establishing a relationship between the distance entry rate, and its spatial and temporal penalty. The optimal deployment of fast charging stations is modeled by a non-linear exact optimization problem that will determine the optimal locations for FCS construction. A proposed method based on a genetic algorithm is presented to solve this problem. The simulation results prove the effectiveness of the proposed algorithm in maximizing the profit for the FCS construction company, considering the power grid constraints. https://isee.ui.ac.ir/article_29366_e399d5779c4aca26e1566038810d9df7.pdf