Photovoltaic energy has become a key pillar in the transition to sustainable energy systems, driven by the need for efficient energy conversion and the reduction of dependency on fossil fuels. Maximum Power Point Tracking (MPPT) is central to optimizing the performance of photovoltaic systems by ensuring the maximum extraction of solar energy, even under fluctuating environmental conditions. This review provides a comprehensive analysis of MPPT algorithms developed and refined over the past decade (2015–2025), highlighting major breakthroughs in algorithmic approaches, from conventional methods such as Perturb and Observe (P&O) and Incremental Conductance (IncCond) to more advanced techniques incorporating artificial intelligence, fuzzy logic, and hybrid systems. The paper evaluates the evolution of MPPT techniques, focusing on their effectiveness in real-world applications, particularly in optimizing photovoltaic output under diverse operating conditions such as partial shading, temperature variations, and rapid irradiance changes. Furthermore, it discusses the ongoing challenges in the field and the promising directions for future research, aiming to further enhance the reliability and efficiency of solar power systems worldwide.
Bouksaim et al. (Fri,) studied this question.