Hybrid adaptive dwarf mongoose optimization with whale optimization algorithm for extracting photovoltaic parameters

This article proposed adaptive hybrid dwarf mongoose optimization (DMO) with whale optimization algorithm (DMOWOA) to extract solar cell model parameters. In DMOWOA, the whale optimization algorithm (WOA) is used to enhance the capability of DMO in escaping local optima, while introducing inertial w...

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Vydáno v:AIMS energy Ročník 12; číslo 1; s. 84 - 118
Hlavní autoři: Chen, Shijian, Zhou, Yongquan, Luo, Qifang
Médium: Journal Article
Jazyk:angličtina
Vydáno: AIMS Press 2024
Témata:
dwarf mongoose optimization
hybrid metaheuristic algorithm
parameters extraction
photovoltaic models
whale optimization algorithm
ISSN:2333-8334, 2333-8334
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Shrnutí:This article proposed adaptive hybrid dwarf mongoose optimization (DMO) with whale optimization algorithm (DMOWOA) to extract solar cell model parameters. In DMOWOA, the whale optimization algorithm (WOA) is used to enhance the capability of DMO in escaping local optima, while introducing inertial weights to achieve a balance between exploration and exploitation. The DMOWOA performances are tested through the solving of the single diode model, double diode model, and photovoltaic (PV) modules. Finally, the DMOWOA is compared with six well-known algorithms and other optimization methods. The experimental results demonstrate that the proposed DMOWOA exhibits remarkable competitiveness in convergence speed, robustness, and accuracy.
ISSN:2333-8334
2333-8334
DOI:10.3934/energy.2024005