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The successful adoption of Electric Vehicles (EVs) worldwide largely depends on the efficiency of Electric Vehicle Charging Station (EVCS) infrastructure. Ultra-fast charging facilities are particularly beneficial for public services as they significantly reduce user waiting times. It is crucial to strategically position charging stations (CS) in optimal locations with a sufficient number of chargers to ensure both secure power system operation and improved EV services. This paper introduces a multi-scenario-based planning model for ultra-fast EVCS (UF-EVCS), taking into consideration security constraints related to the power system, CS, and EV. To address uncertainties in EV charging behavior, multiple scenarios are generated using the 2 m-Point Estimate Method. The objective is to minimize the total cost of UF-EVCS planning, including installation, operational, and energy loss costs. The optimal CS locations and the optimal number of chargers are determined using the Exponential Particle Swarm Optimization (EPSO) technique.

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Multi-scenario Based Optimal Allocation of Ultra-Fast Electric Vehicle Charging Station in the Distribution Network

  • 会议论文

  • 发表日期：

    2025年

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  • Sharmistha Nandi,
  • Sriparna Roy Ghatak,
  • Parimal Acharjee,
  • Fernando Lopes

摘要

The successful adoption of Electric Vehicles (EVs) worldwide largely depends on the efficiency of Electric Vehicle Charging Station (EVCS) infrastructure. Ultra-fast charging facilities are particularly beneficial for public services as they significantly reduce user waiting times. It is crucial to strategically position charging stations (CS) in optimal locations with a sufficient number of chargers to ensure both secure power system operation and improved EV services. This paper introduces a multi-scenario-based planning model for ultra-fast EVCS (UF-EVCS), taking into consideration security constraints related to the power system, CS, and EV. To address uncertainties in EV charging behavior, multiple scenarios are generated using the 2 m-Point Estimate Method. The objective is to minimize the total cost of UF-EVCS planning, including installation, operational, and energy loss costs. The optimal CS locations and the optimal number of chargers are determined using the Exponential Particle Swarm Optimization (EPSO) technique.