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Title	A Reinforcement Learning-Based Strategy For The Optimal Placement Of Electric Vehicle Charging Stations In Smart City For Urban Planning
ID_Doc	4042
Authors	Pan S.; Maity S.P.; Ioannou I.I.; Vassiliou V.; Adhvaryu K.
Year	2024
Published	2024 Asian Conference on Communication and Networks, ASIANComNet 2024
DOI	http://dx.doi.org/10.1109/ASIANComNet63184.2024.10811079
Abstract	In this paper, we present a reinforcement learning (RL)-based strategy for placing optimal charging stations (CS) of electric vehicles (EVs) in the case of Urban planning and smart city development under digital twin. The objective is to minimize the energy required by EVs to reach the CS for recharging. Our approach shows the efficacy of computationally identified CS placement over random placement. Extensive research has demonstrated that an RL-based strategy yields better results in identifying suitable CS locations than random positioning. Based on our investigation, the proposed method finds the most effective positions and some alternative locations for the placement of CS. This study presents a novel approach with 2 0. 9 7% enhancement in energy efficiency compared to related research findings. Furthermore, our proposed approach demonstrates expedited attainment of an optimal policy, outperforming existing literature. © 2024 IEEE.
Author Keywords	Charging station placement; energy consumption; epsilon-greedy policy; reinforcement learning; smart city; urban planning

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