Parameter Estimation of Photovoltaic Models via Cuckoo Search

Since conventional methods are incapable of estimating the parameters of Photovoltaic (PV) models with high accuracy, bioinspired algorithms have attracted significant attention in the last decade. Cuckoo Search (CS) is invented based on the inspiration of brood parasitic behavior of some cuckoo spe...

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Main Authors: Jieming Ma, T. O. Ting, Ka Lok Man, Nan Zhang, Sheng-Uei Guan, Prudence W. H. Wong
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2013/362619
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author Jieming Ma
T. O. Ting
Ka Lok Man
Nan Zhang
Sheng-Uei Guan
Prudence W. H. Wong
author_facet Jieming Ma
T. O. Ting
Ka Lok Man
Nan Zhang
Sheng-Uei Guan
Prudence W. H. Wong
author_sort Jieming Ma
collection DOAJ
description Since conventional methods are incapable of estimating the parameters of Photovoltaic (PV) models with high accuracy, bioinspired algorithms have attracted significant attention in the last decade. Cuckoo Search (CS) is invented based on the inspiration of brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior. In this paper, a CS-based parameter estimation method is proposed to extract the parameters of single-diode models for commercial PV generators. Simulation results and experimental data show that the CS algorithm is capable of obtaining all the parameters with extremely high accuracy, depicted by a low Root-Mean-Squared-Error (RMSE) value. The proposed method outperforms other algorithms applied in this study.
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institution Kabale University
issn 1110-757X
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publishDate 2013-01-01
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series Journal of Applied Mathematics
spelling doaj-art-eaf3ca844da04bcd99035f35a7d8e5ee2025-02-03T01:12:26ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/362619362619Parameter Estimation of Photovoltaic Models via Cuckoo SearchJieming Ma0T. O. Ting1Ka Lok Man2Nan Zhang3Sheng-Uei Guan4Prudence W. H. Wong5Department of Computer Science, University of Liverpool, Ashton Building, Ashton Street, Liverpool, L69 3BX, UKXi’an Jiaotong-Liverpool University, 111 Ren’ai Road, Suzhou Dushu Lake, HET, Jiangsu Province 215123, ChinaXi’an Jiaotong-Liverpool University, 111 Ren’ai Road, Suzhou Dushu Lake, HET, Jiangsu Province 215123, ChinaXi’an Jiaotong-Liverpool University, 111 Ren’ai Road, Suzhou Dushu Lake, HET, Jiangsu Province 215123, ChinaXi’an Jiaotong-Liverpool University, 111 Ren’ai Road, Suzhou Dushu Lake, HET, Jiangsu Province 215123, ChinaDepartment of Computer Science, University of Liverpool, Ashton Building, Ashton Street, Liverpool, L69 3BX, UKSince conventional methods are incapable of estimating the parameters of Photovoltaic (PV) models with high accuracy, bioinspired algorithms have attracted significant attention in the last decade. Cuckoo Search (CS) is invented based on the inspiration of brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior. In this paper, a CS-based parameter estimation method is proposed to extract the parameters of single-diode models for commercial PV generators. Simulation results and experimental data show that the CS algorithm is capable of obtaining all the parameters with extremely high accuracy, depicted by a low Root-Mean-Squared-Error (RMSE) value. The proposed method outperforms other algorithms applied in this study.http://dx.doi.org/10.1155/2013/362619
spellingShingle Jieming Ma
T. O. Ting
Ka Lok Man
Nan Zhang
Sheng-Uei Guan
Prudence W. H. Wong
Parameter Estimation of Photovoltaic Models via Cuckoo Search
Journal of Applied Mathematics
title Parameter Estimation of Photovoltaic Models via Cuckoo Search
title_full Parameter Estimation of Photovoltaic Models via Cuckoo Search
title_fullStr Parameter Estimation of Photovoltaic Models via Cuckoo Search
title_full_unstemmed Parameter Estimation of Photovoltaic Models via Cuckoo Search
title_short Parameter Estimation of Photovoltaic Models via Cuckoo Search
title_sort parameter estimation of photovoltaic models via cuckoo search
url http://dx.doi.org/10.1155/2013/362619
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