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

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.