Parameter Extraction for Photovoltaic Models with Flood-Algorithm-Based Optimization DOI Creative Commons
Yacine Bouali, Basem Alamri

Mathematics, Journal Year: 2024, Volume and Issue: 13(1), P. 19 - 19

Published: Dec. 25, 2024

Accurately modeling photovoltaic (PV) cells is crucial for optimizing PV systems. Researchers have proposed numerous mathematical models of to facilitate the design and simulation Usually, a cell modeled by equivalent electrical circuit with specific parameters, which are often unknown; this leads formulating an optimization problem that addressed through metaheuristic algorithms identify cell/module parameters accurately. This paper introduces flood algorithm (FLA), novel efficient approach, extract various models, including single-diode, double-diode, three-diode module configurations. The FLA’s performance systematically evaluated against nine recently developed comprehensive comparative statistical analyses. results highlight superior convergence speed, global search capability, robustness. study explores two distinct objective functions enhance accuracy: one based on experimental current–voltage data another integrating Newton–Raphson method. Applying Newton–Raphson-based function reduced root-mean-square error (RMSE) more effectively than traditional methods. These findings establish FLA as computationally reliable approach parameter extraction, promising implications advancing system simulation.

Language: Английский

A reinforcement learning-based ranking teaching-learning-based optimization algorithm for parameters estimation of photovoltaic models DOI
Haoyu Wang, Xiaobing Yu,

Yangchen Lu

et al.

Swarm and Evolutionary Computation, Journal Year: 2025, Volume and Issue: 93, P. 101844 - 101844

Published: Jan. 9, 2025

Language: Английский

Citations

2
Dynamic opposition learning-based rank-driven teaching learning optimizer for parameter extraction of photovoltaic models DOI Creative Commons
Xu‐Ming Wang, Wen Zhang

Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 117, P. 325 - 339

Published: Jan. 16, 2025

Language: Английский

Citations

1
Parameter Extraction for Photovoltaic Models with Flood-Algorithm-Based Optimization DOI Creative Commons
Yacine Bouali, Basem Alamri

Mathematics, Journal Year: 2024, Volume and Issue: 13(1), P. 19 - 19

Published: Dec. 25, 2024

Accurately modeling photovoltaic (PV) cells is crucial for optimizing PV systems. Researchers have proposed numerous mathematical models of to facilitate the design and simulation Usually, a cell modeled by equivalent electrical circuit with specific parameters, which are often unknown; this leads formulating an optimization problem that addressed through metaheuristic algorithms identify cell/module parameters accurately. This paper introduces flood algorithm (FLA), novel efficient approach, extract various models, including single-diode, double-diode, three-diode module configurations. The FLA’s performance systematically evaluated against nine recently developed comprehensive comparative statistical analyses. results highlight superior convergence speed, global search capability, robustness. study explores two distinct objective functions enhance accuracy: one based on experimental current–voltage data another integrating Newton–Raphson method. Applying Newton–Raphson-based function reduced root-mean-square error (RMSE) more effectively than traditional methods. These findings establish FLA as computationally reliable approach parameter extraction, promising implications advancing system simulation.

Language: Английский

Citations

1