Energy optimization of PV systems under partial shading conditions using various technique-based MPPT methods.

This research project presents a comprehensive evaluation and implementation framework for optimizing energy extraction in photovoltaic (PV) systems operating under partial shading conditions (PSC). Under non-uniform irradiance, PV array characteristics exhibit multiple local power peaks alongside a single global maximum power point (GMPP), which conventional tracking algorithms often fail to identify. To address this limitation, this work provides structuring and simulation-based guidance for analyzing various advanced Maximum Power Point Tracking (MPPT) techniques, including metaheuristic algorithms, hybrid schemes, and soft-computing methods. The research direction focuses on modeling a multi-array PV configuration integrated with DC-DC boost converters to evaluate tracking efficiency, convergence speed, and steady-state oscillations. Through systematic performance review and comparative

analysis, the project establishes a robust methodology for selecting optimal MPPT controllers based on environmental dynamics. The implementation support framework assists in designing MATLAB/Simulink models to validate the transient and steady-state response of each technique. Ultimately, this study contributes to the systematic design of highly efficient solar energy harvesting systems, offering clear guidance for mitigating mismatch losses and enhancing overall system reliability under complex shading profiles.

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