Publication: Efficient optimization for perturb and observation (P&O) algorithm in MPPT to track maximum power point tracking under rapid change of irradiance
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Date
2024-07
Authors
Muhammad Nur Faiz Raihan bin Zolkefl
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Abstract
Photovoltaic (PV) systems are integral to sustainable energy production, necessitating efficient Maximum Power Point Tracking (MPPT) algorithms for optimal
performance. The Perturb and Observe (P&O) algorithm is widely adopted due to its simplicity and affordability, yet it faces challenges in adapting to rapid fluctuations in solar irradiance. This study aims to enhance the P&O algorithm's performance under dynamic irradiance conditions by optimizing its adaptability and reducing oscillations around the maximum power point (MPP). The study utilized MATLAB and Simulink to develop and validate the improved P&O algorithm, demonstrating significant improvements in power output and efficiency compared to the conventional method. During rapid increases in irradiance, the proposed algorithm achieved a more stable power output with minimal oscillations, outperforming the traditional method. Overall, the proposed enhancements improved the efficiency of the MPPT system by reducing the response time to irradiance changes, ensuring quicker adaptation and stable power output under varying conditions. By leveraging these simulations, the study develops and validates an improved P&O algorithm tailored for MPPT in changing environmental settings, aiming to bolster the reliability and efficiency of MPPT systems and advance the integration of solar energy solutions into real-world applications