A novel equilibrium optimizer for tracking the maximum power of a photovoltaic system under non-uniform conditions

Unavoidably, solar energy is at the top of replenished energies. When light rays strike the modules of a solar panel, the Power-Voltage curve is formed. This curve is uniform in a similar irradiation case, but it is non-uniform in the case of shading. Several methods, including conventional and modern methods, can be used to extract the maximum possible power from a solar array; however, in the case of non-uniform shape, conventional methods such as P & O result in inefficiency and poor tracking of the maximum power point, as well as being trapped in a local maximum in the non-linear PV curve. In this study, one of the most recent meta-heuristic algorithms that utilize a physical principle, Equilibrium optimizer (EO), was utilized. To track the maximum power point on the PV curve, it was compared to two other metaheuristic algorithms, Grey Wolf optimizer (GWO) and Particle Swarm optimization (PSO). Experiments conducted in Matlab/Simulink demonstrated the superiority of EO over other algorithms in terms of tracking and searching efficiency during the exploration and exploitation phases.