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<p>In this work, the study gives attention for improvement of the Maximum Power Point Tracking (MPPT) using the Perturb and Observe (P&amp;O) algorithm based MPPT applied to solar power generation system (SPGS). The algorithm components are refined, outcomes of the resultant optimized values are compared to address challenges in optimizing power, voltage and efficiency with the research. Further to improve this performance, Fractional Order Proportional Integral Derivative (FOPID) criteria are tuned using optimization techniques such as Black Hole (BH) Optimization, Jaya Optimization Algorithm (JOA), and Sunflower Optimization (SFO). Selection of optimal power and voltage values was aided by these methods. Limitations of the study include the exclusion of dynamic environmental changes in the analysis, and the potential non specificity of optimization algorithms for all SPGS scenarios considered. SPGS offers an opportunity to explore more dynamic models, as well as alternative algorithms, to improve the power and voltage management done in SPGS.</p>

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Evaluation of optimization algorithms for power and voltage in solar power generation system: FOPID controller and MPPT-based P&O algorithm

  • 期刊论文

  • 发表日期：

    2025年2月11日

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  • Zahraa Ali Dawood,
  • Samuel Nii Tackie,
  • Kamil Dimililer

摘要

In this work, the study gives attention for improvement of the Maximum Power Point Tracking (MPPT) using the Perturb and Observe (P&O) algorithm based MPPT applied to solar power generation system (SPGS). The algorithm components are refined, outcomes of the resultant optimized values are compared to address challenges in optimizing power, voltage and efficiency with the research. Further to improve this performance, Fractional Order Proportional Integral Derivative (FOPID) criteria are tuned using optimization techniques such as Black Hole (BH) Optimization, Jaya Optimization Algorithm (JOA), and Sunflower Optimization (SFO). Selection of optimal power and voltage values was aided by these methods. Limitations of the study include the exclusion of dynamic environmental changes in the analysis, and the potential non specificity of optimization algorithms for all SPGS scenarios considered. SPGS offers an opportunity to explore more dynamic models, as well as alternative algorithms, to improve the power and voltage management done in SPGS.