An adaptive differential evolution with decomposition for photovoltaic parameter extraction

Photovoltaic (PV) parameter extraction plays a key role in establishing accurate and reliable PV models based on the manufacturer's current-voltage data. Owning to the characteristics such as implicit and nonlinear of the PV model, it remains a challenging and research-meaningful task in PV sys...

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Autores principales:	Zhen Yan, Shuijia Li, Wenyin Gong
Formato:	article
Lenguaje:	EN
Publicado:	AIMS Press 2021
Materias:	parameter extraction photovoltaic model decomposition differential evolution adaptation Biotechnology TP248.13-248.65 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/9ef60666bd914cf99b4465d130b9aa47
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spelling	oai:doaj.org-article:9ef60666bd914cf99b4465d130b9aa472021-11-23T01:57:21ZAn adaptive differential evolution with decomposition for photovoltaic parameter extraction10.3934/mbe.20213641551-0018https://doaj.org/article/9ef60666bd914cf99b4465d130b9aa472021-08-01T00:00:00Zhttps://www.aimspress.com/article/doi/10.3934/mbe.2021364?viewType=HTMLhttps://doaj.org/toc/1551-0018Photovoltaic (PV) parameter extraction plays a key role in establishing accurate and reliable PV models based on the manufacturer's current-voltage data. Owning to the characteristics such as implicit and nonlinear of the PV model, it remains a challenging and research-meaningful task in PV system optimization. Despite there are many methods that have been developed to solve this problem, they are often consuming a great deal of computing resources for more satisfactory results. To reduce computing resources, in this paper, an advanced differential evolution with search space decomposition is developed to effectively extract the unknown parameters of PV models. In proposed approach, a recently proposed advanced differential evolution algorithm is used as a solver. In addition, a search space decomposition technique is introduced to reduce the dimension of the problem, thereby reducing the complexity of the problem. Three different PV cell models are selected for verifying the performance of proposed approach. The experimental result is firstly compared with some representative differential evolution algorithms that do not use search space decomposition technique, which demonstrates the effectiveness of the search space decomposition. Moreover, the comparison results with some reported well-established parameter extraction methods suggest that the proposed approach not only obtains accurate and reliable parameters, but also uses the least computational resources.Zhen Yan Shuijia LiWenyin GongAIMS Pressarticleparameter extractionphotovoltaic modeldecompositiondifferential evolutionadaptationBiotechnologyTP248.13-248.65MathematicsQA1-939ENMathematical Biosciences and Engineering, Vol 18, Iss 6, Pp 7363-7388 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	parameter extraction photovoltaic model decomposition differential evolution adaptation Biotechnology TP248.13-248.65 Mathematics QA1-939
spellingShingle	parameter extraction photovoltaic model decomposition differential evolution adaptation Biotechnology TP248.13-248.65 Mathematics QA1-939 Zhen Yan Shuijia Li Wenyin Gong An adaptive differential evolution with decomposition for photovoltaic parameter extraction
description	Photovoltaic (PV) parameter extraction plays a key role in establishing accurate and reliable PV models based on the manufacturer's current-voltage data. Owning to the characteristics such as implicit and nonlinear of the PV model, it remains a challenging and research-meaningful task in PV system optimization. Despite there are many methods that have been developed to solve this problem, they are often consuming a great deal of computing resources for more satisfactory results. To reduce computing resources, in this paper, an advanced differential evolution with search space decomposition is developed to effectively extract the unknown parameters of PV models. In proposed approach, a recently proposed advanced differential evolution algorithm is used as a solver. In addition, a search space decomposition technique is introduced to reduce the dimension of the problem, thereby reducing the complexity of the problem. Three different PV cell models are selected for verifying the performance of proposed approach. The experimental result is firstly compared with some representative differential evolution algorithms that do not use search space decomposition technique, which demonstrates the effectiveness of the search space decomposition. Moreover, the comparison results with some reported well-established parameter extraction methods suggest that the proposed approach not only obtains accurate and reliable parameters, but also uses the least computational resources.
format	article
author	Zhen Yan Shuijia Li Wenyin Gong
author_facet	Zhen Yan Shuijia Li Wenyin Gong
author_sort	Zhen Yan
title	An adaptive differential evolution with decomposition for photovoltaic parameter extraction
title_short	An adaptive differential evolution with decomposition for photovoltaic parameter extraction
title_full	An adaptive differential evolution with decomposition for photovoltaic parameter extraction
title_fullStr	An adaptive differential evolution with decomposition for photovoltaic parameter extraction
title_full_unstemmed	An adaptive differential evolution with decomposition for photovoltaic parameter extraction
title_sort	adaptive differential evolution with decomposition for photovoltaic parameter extraction
publisher	AIMS Press
publishDate	2021
url	https://doaj.org/article/9ef60666bd914cf99b4465d130b9aa47
work_keys_str_mv	AT zhenyan anadaptivedifferentialevolutionwithdecompositionforphotovoltaicparameterextraction AT shuijiali anadaptivedifferentialevolutionwithdecompositionforphotovoltaicparameterextraction AT wenyingong anadaptivedifferentialevolutionwithdecompositionforphotovoltaicparameterextraction AT zhenyan adaptivedifferentialevolutionwithdecompositionforphotovoltaicparameterextraction AT shuijiali adaptivedifferentialevolutionwithdecompositionforphotovoltaicparameterextraction AT wenyingong adaptivedifferentialevolutionwithdecompositionforphotovoltaicparameterextraction
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An adaptive differential evolution with decomposition for photovoltaic parameter extraction

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