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A Modified Gradient Search Rule Based on the Quasi-Newton Method and a New Local Search Technique to Improve the Gradient-Based Algorithm: Solar Photovoltaic Parameter Extraction

Author

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  • Bushra Shakir Mahmood

    (Department of Mathematics, College of Computer Sciences and Mathematics, Tikrit University, Tikrit 34001, Iraq)

  • Nazar K. Hussein

    (Department of Mathematics, College of Computer Sciences and Mathematics, Tikrit University, Tikrit 34001, Iraq)

  • Mansourah Aljohani

    (College of Computer Science and Engineering, Taibah University, Yanbu 46421, Saudi Arabia)

  • Mohammed Qaraad

    (Computer Science Department, Faculty of Science, Abdelmalek Essaadi University, Tetouan 93000, Morocco
    Department of Computer Science, Faculty of Science, Amran University, Amran 9677, Yemen)

Abstract

Harnessing solar energy efficiently via photovoltaic (PV) technology is pivotal for future sustainable energy. Accurate modeling of PV cells entails an optimization problem due to the multimodal and nonlinear characteristics of the cells. This study introduces the Multi-strategy Gradient-Based Algorithm (MAGBO) for the precise parameter estimation of solar PV systems. MAGBO incorporates a modified gradient search rule (MGSR) inspired by the quasi-Newton approach, a novel refresh operator (NRO) for improved solution quality, and a crossover mechanism balancing exploration and exploitation. Validated through CEC2021 test functions, MAGBO excelled in global optimization. To further validate and underscore the reliability of MAGBO, we utilized data from the PVM 752 GaAs thin-film cell and the STP6-40/36 module. The simulation parameters were discerned using 44 I-V pairs from the PVM 752 cell and diverse data from the STP6-40/36 module tested under different conditions. Consistency between simulated and observed I-V and P-V curves for the STM6-40/36 and PVM 752 models validated MAGBO’s accuracy. In application, MAGBO attained an RMSE of 9.8 × 10 −4 for double-diode and single-diode modules. For Photowatt-PWP, STM6-40/36, and PVM 752 models, RMSEs were 2.4 × 10 −3 , 1.7 × 10 −3 , and 1.7 × 10 −3 , respectively. Against prevalent methods, MAGBO exhibited unparalleled precision and reliability, advocating its superior utility for intricate PV data analysis.

Suggested Citation

  • Bushra Shakir Mahmood & Nazar K. Hussein & Mansourah Aljohani & Mohammed Qaraad, 2023. "A Modified Gradient Search Rule Based on the Quasi-Newton Method and a New Local Search Technique to Improve the Gradient-Based Algorithm: Solar Photovoltaic Parameter Extraction," Mathematics, MDPI, vol. 11(19), pages 1-40, October.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:19:p:4200-:d:1255653
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    References listed on IDEAS

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