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Abstract <p>Enhancing the efficiency of photovoltaic (PV) systems is a crucial step in advancing the smart grid towards sustainable energy generation. This inquiry underscores the critical importance of accurate parameter extraction and optimization in attaining optimum performance for photovoltaic systems within modern energy grids. Modeling PV modules poses inherent challenges due to their nonlinear current-voltage characteristics and the limited availability of cell datasheet information. To address these issues, this work specifically targets the extraction of single diode model (SDM) parameters in PV modules using an innovative hybrid metaheuristic algorithm, FIS-MTBO, which represents our major contribution. This novel approach integrates the Fully Informed Search (FIS) algorithm with the Mountaineering Team Based Optimization (MTBO). Thorough analysis via two simulated case studies demonstrates the algorithm’s effectiveness, outperforming eleven established algorithms in consistency and precision. These results underscore the potential of the FIS-MTBO algorithm to improve the optimization of PV systems and propel the advancement of sustainable energy endeavors.</p>

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Efficient Parameter Estimation for Photovoltaic Single Diode Model using a New Hybrid Optimization Technique

  • 期刊论文

  • 发表日期：

    2025年8月1日

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  • B. Lekouaghet,
  • F. Brioua,
  • M. Haddad,
  • B. Babes,
  • N. Hamouda,
  • M. Benghanem

摘要

Abstract

Enhancing the efficiency of photovoltaic (PV) systems is a crucial step in advancing the smart grid towards sustainable energy generation. This inquiry underscores the critical importance of accurate parameter extraction and optimization in attaining optimum performance for photovoltaic systems within modern energy grids. Modeling PV modules poses inherent challenges due to their nonlinear current-voltage characteristics and the limited availability of cell datasheet information. To address these issues, this work specifically targets the extraction of single diode model (SDM) parameters in PV modules using an innovative hybrid metaheuristic algorithm, FIS-MTBO, which represents our major contribution. This novel approach integrates the Fully Informed Search (FIS) algorithm with the Mountaineering Team Based Optimization (MTBO). Thorough analysis via two simulated case studies demonstrates the algorithm’s effectiveness, outperforming eleven established algorithms in consistency and precision. These results underscore the potential of the FIS-MTBO algorithm to improve the optimization of PV systems and propel the advancement of sustainable energy endeavors.