Parameter Extraction for Photovoltaic Models with Flood-Algorithm-Based Optimization
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| Publicado en: | Mathematics vol. 13, no. 1 (2025), p. 19 |
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| Autor Principal: | |
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| Publicado: |
MDPI AG
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| Acceso en liña: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 001 | 3153800285 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2227-7390 | ||
| 024 | 7 | |a 10.3390/math13010019 |2 doi | |
| 035 | |a 3153800285 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231533 |2 nlm | ||
| 100 | 1 | |a Bouali, Yacine |u Department of Electrical Engineering, University of Science and Technology Houari Boumediene, P.O. Box 32, El-Alia, Algiers 16111, Algeria | |
| 245 | 1 | |a Parameter Extraction for Photovoltaic Models with Flood-Algorithm-Based Optimization | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Accurately modeling photovoltaic (PV) cells is crucial for optimizing PV systems. Researchers have proposed numerous mathematical models of PV cells to facilitate the design and simulation of PV systems. Usually, a PV cell is modeled by equivalent electrical circuit models with specific parameters, which are often unknown; this leads to formulating an optimization problem that is addressed through metaheuristic algorithms to identify the PV cell/module parameters accurately. This paper introduces the flood algorithm (FLA), a novel and efficient optimization approach, to extract parameters for various PV models, including single-diode, double-diode, and three-diode models and PV module configurations. The FLA’s performance is systematically evaluated against nine recently developed optimization algorithms through comprehensive comparative and statistical analyses. The results highlight the FLA’s superior convergence speed, global search capability, and robustness. This study explores two distinct objective functions to enhance accuracy: one based on experimental current–voltage data and another integrating the Newton–Raphson method. Applying metaheuristic algorithms with the Newton–Raphson-based objective function reduced the root-mean-square error (RMSE) more effectively than traditional methods. These findings establish the FLA as a computationally efficient and reliable approach to PV parameter extraction, with promising implications for advancing PV system design and simulation. | |
| 653 | |a Parameter identification | ||
| 653 | |a Accuracy | ||
| 653 | |a Configuration management | ||
| 653 | |a Costs | ||
| 653 | |a Fossil fuels | ||
| 653 | |a Root-mean-square errors | ||
| 653 | |a Knowledge sharing | ||
| 653 | |a Renewable resources | ||
| 653 | |a Newton-Raphson method | ||
| 653 | |a Systems design | ||
| 653 | |a Numerical analysis | ||
| 653 | |a Algorithms | ||
| 653 | |a Methods | ||
| 653 | |a Circuits | ||
| 653 | |a Alternative energy sources | ||
| 653 | |a Energy resources | ||
| 653 | |a Design optimization | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Optimization algorithms | ||
| 653 | |a Climate change | ||
| 653 | |a Heuristic methods | ||
| 653 | |a Photovoltaic cells | ||
| 653 | |a Parameter estimation | ||
| 700 | 1 | |a Alamri, Basem |u Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia; <email>b.alamri@tu.edu.sa</email> | |
| 773 | 0 | |t Mathematics |g vol. 13, no. 1 (2025), p. 19 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3153800285/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3153800285/fulltextwithgraphics/embedded/H09TXR3UUZB2ISDL?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3153800285/fulltextPDF/embedded/H09TXR3UUZB2ISDL?source=fedsrch |