首页|Balancing Exploration-Exploitation of Multi-verse Optimizer for Parameter Extraction on Photovoltaic Models

Balancing Exploration-Exploitation of Multi-verse Optimizer for Parameter Extraction on Photovoltaic Models

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Extracting photovoltaic(PV)model parameters based on the measured voltage and current information is crucial in the simu-lation and management of PV systems.To accurately and reliably extract the unknown parameters of different PV models,this paper proposes an improved multi-verse optimizer that integrates an iterative chaos map and the Nelder-Mead simplex method,INMVO.Quantitative experiments verified that the proposed INMVO fueled by both mechanisms has more affluent populations and a more reasonable balance between exploration and exploitation.Further,to verify the feasibility and com-petitiveness of the proposal,this paper employed INMVO to extract the unknown parameters on single-diode,double-diode,three-diode,and PV module four well-known PV models,and the high-performance techniques are selected for comparison.In addition,the Wilcoxon signed-rank and Friedman tests were employed to test the experimental results statistically.Various evaluation metrics,such as root means square error,relative error,absolute error,and statistical test,demonstrate that the proposed INMVO works effectively and accurately to extract the unknown parameters on different PV models compared to other techniques.In addition,the capability of INMVO to stably and accurately extract unknown parameters was also veri-fied on three commercial PV modules under different irradiance and temperatures.In conclusion,the proposal in this paper can be implemented as an advanced and reliable tool for extracting the unknown parameters of different PV models.Note that the source code of INMVO is available at https://github.com/woniuzuioupao/INMVO.

Photovoltaic modelsMulti-verse optimizerNelder-Mead simplexIterative chaos map

Yan Han、Weibin Chen、Ali Asghar Heidari、Huiling Chen、Xin Zhang

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College of Computer Science and Artificial Intelligence,Wenzhou University,Wenzhou 325035,China

Key Laboratory of Intelligent Informatics for Safety &Emergency of Zhejiang Province,Wenzhou University,Wenzhou,China

Key Lab of Biohealth Materials and Chemistry of Wenzhou,Wenzhou University,Wenzhou,China

School of Surveying and Geospatial Engineering,College of Engineering,University of Tehran,Tehran,Iran

School of Biomedical Engineering,National Engineering Research Center of Ophthalmology and Optometry,Eye Hospital,Wenzhou Medical University,Wenzhou 325027,China

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Natural science Foundation of Zhejiang ProvinceNatural science Foundation of Zhejiang ProvinceNational Natural Science Foundation of ChinaScience and Technology Plan Project of Wenzhou,China

LY21F020001LZ22F02000562076185ZG2020026

2024

10.1007/s42235-024-00479-6

仿生工程学报(英文版)
吉林大学

仿生工程学报(英文版)

CSTPCDEI
影响因子：0.837
ISSN：1672-6529
年,卷(期)：2024.21(2)
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