Metaheuristic Algorithms for Evaluating the Effect of Electric Vehicle Charging Infrastructures in Distribution Networks

To address the effect of electric vehicle (EV) load on distribution system efficient optimization techniques are required. In this paper, an attempt is made to work with various new optimization techniques for minimizing the detrimental effect of EV charging station (EVCS) load on the electrical network. The operating conditions of the distribution network, that is, voltage stability, reliability and power loss (VRP) index are optimized in this work in a framework of multiple objectives with various technical constraints. Although many optimization approaches have been developed in recent years, eight well-known techniques are employed in the present work such as modified teaching-learner-based optimization (MTLBO), JAYA, modified JAYA (MJAYA), ant–lion optimization (ALO), whale optimization technique (WOT), grasshopper optimization technique (GOT), modified whale optimization algorithm (MWOA), and hybrid whale particle swarm optimization (HWPSOA). All the eight techniques’ performance is compared under two different cases of operations by testing the objective function on the modified IEEE 33 bus distribution system using MATLAB software. The numerical solutions obtained by the HWPSOA indicate the suitability and effectiveness for optimizing the specified complex multi-objective function compared to other techniques.