Research Area:  Metaheuristic Computing

Abstract:

This research focuses on a photovoltaic system that powers an Electric Vehicle when moving in realistic scenarios with partial shading conditions. The main goal is to find an efficient control scheme to allow the solar generator producing the maximum amount of power achievable. The first contribution of this paper is the mathematical modelling of the photovoltaic system, its function and its features, considering the synthesis of the step-up converter and the maximum power point tracking analysis. This research looks at two intelligent control strategies to get the most power out, even with shading areas. Specifically, we show how to apply two evolutionary algorithms for this control. They are the “particle swarm optimization method” and the “grey wolf optimization method”. These algorithms were tested and evaluated when a battery storage system in an Electric Vehicle is fed through a photovoltaic system. The Simulink/Matlab tool is used to execute the simulation phases and to quantify the performances of each of these control systems. Based on our simulation tests, the best method is identified.

Keywords:  
optimization algorithm
control system
renewable energy
PSO
GWO
battery storage energy
electric vehicle

Author(s) Name:  Habib Kraiem , Flah Aymen, Lobna Yahya, Alicia Triviño, Mosleh Alharthi and Sherif S. M. Ghoneim

Publisher name:  MDPI

DOI:  10.3390/app11167732

Volume Information:  11(16), 7732

Paper Link:   https://www.mdpi.com/2076-3417/11/16/7732