Load Suitability Index-based Optimal Placement of Electric Vehicle Charging Stations in a 16-Bus Radial Distribution System

Abstract

The exponential increasing adoption of EVs poses various difficulties in terms of the operation of RDS because of their negative impact on power losses, voltage profile deterioration, and feeder overload. The adoption of Electric Vehicle Charging Stations (EVCSs) at RDS in optimal methodology plays a vital role in ensuring secure and efficient network operation. In this regard, a two-stage technique is presented in this study to optimize the locations and sizes of EVCSs in a 16-bus RDS. In the first phase, Load Suitability Index (LSI) is created to select the best buses to host the EVCSs considering the factors like load concentration, voltage profile properties, and network structure. In the second phase, Slime Mould Algorithm (SMA) is implemented to optimize the capacities of the EVCSs through minimizing the active power losses while meeting certain operational constraints. Voltage magnitude constraint and branch current constraint are considered as inequality constraints in the proposed problem formulation. For analyzing the network, a Forward-Backward Sweep (FBS) load flow solution technique is used. The simulation findings confirm that the proposed LSI-SMA technique is quite efficient at reducing active power losses and improving voltage profiles relative to the base-case system.