The widespread adoption of Electric Vehicles (EVs) globally relies significantly on effectiveness of the Electric Vehicle Charging Station (EVCS) infrastructure. In this context, fast charging facility is very efficient for public services as it reduces the total waiting time of users. To ensure secure power system operation as well as to enhance EV services, it is essential to position charging stations (CS) in optimal locations with the presence of an adequate number of chargers. In this paper, a multi-scenario planning model for fast EVCS (FEVCS) is developed by considering the security constraints related to power systems, FEVCS, and EV. The proposed model seeks to benefit CS owners, Distribution Network Operators, and EV users. To address the uncertain EV charging behaviour, multiple scenarios are generated using the 2m-Point Estimate Method. The objective of the paper is to minimize the total cost of FEVCS planning in terms of installation, operational, energy loss, and waiting time costs. To identify the accurate CS location and optimal number of chargers, a novel Improved Harris Hawk optimization technique is developed. The overall analysis is tested on real 108-bus Indian distribution network. To prove the efficacy of novel IHHO technique, results are compared with several existing algorithms.


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    Titel :

    Multi-Scenario Based Optimal Planning of Distribution Network Considering Fast Electric Vehicle Charging Station


    Beteiligte:


    Erscheinungsdatum :

    31.07.2024


    Format / Umfang :

    484041 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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