Optimization-based maximum power point tracking for wind energy systems: a comparative study of gray wolf and whale algorithms

Abstract

Maintaining high energy conversion efficiency under varying wind conditions remains a major challenge in wind energy systems. To address this issue, maximum power point tracking (MPPT) techniques have been widely employed Traditional methods frequently depend on precise system parameters or fixed control structures, which may lead to performance degradation. Conversely, optimization-based algorithms can operate under more favorable conditions without requiring specific structures. In this study, two metaheuristic algorithms, the Gray Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA), were implemented as MPPT controllers in the MATLAB/Simulink environment. The main contribution of this study is the evaluation of two metaheuristic optimization algorithms and provision of practical insights into their suitability for wind energy systems. The simulation results showed that the GWO-based method outperformed its WOA counterpart, achieving a higher tracking efficiency of 98.2% and a lower oscillation rate (<2%), indicating higher effectiveness under dynamic wind conditions. © 2027, Polish Academy of Sciences Branch Lublin. All rights reserved.