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Efficient energy extracting from photovoltaic (PV) modules working under partially shading environments are a pivotal concern in solar energy application. This article presents a methodical examination of the crucial role that Maximum Power Point Tracking (MPPT) algorithms contribute in enhancing the performance of solar PV systems in situations involving partial shading. Diverse MPPT algorithms are subjected to thorough analysis, including classical and bio-inspired approaches. Moreover, the article investigates cutting-edge Artificial Intelligence (AI) algorithms based on MPPT strategies that leverage the strengths of multiple algorithms to address the challenges posed by rapidly changing shading patterns. The evaluation encompasses several critical dimensions, such as computational principles, adaptability to varying shading conditions, and the practical complexities associated with real-world implementation. Insights into the benefits and limits of each algorithm type are presented, aiding in the collection of the most suitable MPPT algorithms for explicit PV system configurations and shading scenarios. This study reveals that an MPPT algorithm that is well- suited to the PV system and adjusting partial shading is essential to maximizing energy output. This article promotes sustainable solar energy use by illuminating MPPT techniques.
Leelavathi et al. (Thu,) studied this question.