A High-Performance Hybrid MPPT Method for Rapid Tracking and Steady Power Operation Under Varying Weather Conditions and Load Changes in Photovoltaic Systems

Maximum power point tracking (MPPT) plays a crucial role in the performance of the photovoltaic (PV) output, which decreases dramatically under partial shading conditions (PSCs). The water cycle optimization (WCO) algorithm is presented as a promising solution to address the MPPT problem. However, conventional WCO suffers from a complex parameter tuning process, high oscillations, and low convergence speed when tracking the maximum power point under PSCs and uniform irradiance conditions (UICs), leading to low efficiency and significant power loss. Therefore, an enhanced WCO hybridized with a modified perturb and observe (MP&O) algorithm is introduced as an efficient real-time MPPT method. The enhanced WCO with one dynamic parameter is designed to rapidly identify the global maximum power point (GMPP) under PSCs. The MP&O algorithm, with an adaptive perturbation step size, is used to track the maximum power point under UICs, resulting in minimal oscillations. Moreover, our method employs a load line strategy to address the issue of restarting the tracking process in the MPPT application at load variations, ensuring reliable and rapid GMPP tracking. Extensive experimental tests were conducted to validate the performance of the proposed hybrid method under various UIC, PSC, and complex PSC patterns, as well as during load variations. The results reveal that the method achieves an average tracking time of 0.275 s under UICs and 0.45 s under PSCs, and an average efficiency of 99.90% for all irradiance patterns. A comparative study with other MPPT methods demonstrates the superior performance of the proposed hybrid MPPT method in terms of eleven tracking performance criteria.