Solar Photovoltaic MPPT under irradiance change using a corrected grey wolf optimization algorithm

This paper proposes a new maximum power point tracking technique in PV systems by using the corrected Grey Wolf Optimization (CGWO) algorithm as one of the effective techniques, which could overcome negative issues caused by changing environmental conditions, such as partial shading and dynamic irradiance change. The CGWO-based MPPT algorithm had better tracking accuracy and convergence speed to the GMPP than the conventional techniques, such as the perturb and observe method and incremental conductance method. Extensive simulations prove the effectiveness of the CGWO algorithm with a few parameters; hence, it is guaranteed to be user-friendly and provide robust performance in various operational scenarios. Results confirm that the CGWO-based strategy can considerably improve energy output from PV systems and contribute further to the domain with a reliable and efficient MPPT solution. This opens an avenue for further research into how CGWO applications in real-world PV systems interact and integrate with smart energy grids.