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  • Open Access


    Study on Two-Tier EV Charging Station Recommendation Strategy under Multi-Factor Influence

    Miao Liu, Lei Feng, Yexun Yuan, Ye Liu, Peng Geng*

    Journal on Artificial Intelligence, Vol.5, pp. 181-193, 2023, DOI:10.32604/jai.2023.046066

    Abstract This article aims to address the clustering effect caused by unorganized charging of electric vehicles by adopting a two-tier recommendation method. The electric vehicles (EVs) are classified into high-level alerts and general alerts based on their state of charge (SOC). EVs with high-level alerts have the most urgent charging needs, so the distance to charging stations is set as the highest priority for recommendations. For users with general alerts, a comprehensive EV charging station recommendation model is proposed, taking into account factors such as charging price, charging time, charging station preference, and distance to the charging station. Using real data… More >

  • Open Access


    Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

    Jiulong Sun1, Yanbo Che1,*, Ting Yang1, Jian Zhang2, Yibin Cai1

    Energy Engineering, Vol.120, No.2, pp. 367-384, 2023, DOI:10.32604/ee.2023.023661

    Abstract As the number of electric vehicles (EVs) continues to grow and the demand for charging infrastructure is also increasing, how to improve the charging infrastructure has become a bottleneck restricting the development of EVs. In other words, reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system. Considering the construction and maintenance of the charging station, the distribution network loss of the charging station, and the economic loss on the user side of the EV, this paper takes the node and capacity of… More > Graphic Abstract

    Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

  • Open Access


    Modeling and Experimental Verification of Electric Vehicles Off-Grid Photovoltaic Powered Charging Station

    Essam Hendawi1,*, Sattam Al Otaibi1, Sherif Zaid2,3,4, Ayman Hoballah1, Salah K. ElSayed1, Nagy I. Elkalashy1, Yasser Ahmed1

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1009-1025, 2022, DOI:10.32604/csse.2022.022927

    Abstract With the increasing development of EVs, the energy demand from the conventional utility grid increases in proportion. On the other hand, photovoltaic (PV) energy sources can overcome several problems when charging EVs from the utility grid especially in remote areas. This paper presents an effective photovoltaic stand-alone charging station for EV applications. The proposed charging station incorporates PV array, a lithium-ion battery representing the EV battery, and a lead-acid battery representing the energy storage system (ESS). A bidirectional DC-DC converter is employed for charging/discharging the ESS and a unidirectional DC-DC converter is utilized for charging the EV battery. The proposed… More >

  • Open Access


    A Multi-Objective Decision-Making Approach for the Optimal Location of Electric Vehicle Charging Facilities

    Weiwei Liu1, Yang Tang2, Fei Yang2, Yi Dou3, Jin Wang4,*

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 813-834, 2019, DOI:10.32604/cmc.2019.06754

    Abstract Electric vehicles (EVs) are recognized as one of the most promising technologies worldwide to address the fossil fuel energy resource crisis and environmental pollution. As the initial work of EV charging station (EVCS) construction, site selection plays a vital role in its whole life cycle. In this paper, a multi-objective optimization model for the location layout of EVCSs is established when considering various factors such as user demand, investment cost, soil locations, the emergency charging mileage limit, the actual road condition and service network reliability. The model takes the minimum investment cost and the minimum user charging cost as the… More >

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