An Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions

The output power against voltage curve of the photovoltaic system changes its characteristics under partial shading conditions because of using bypass diodes. These bypass diodes are connected across the PV modules inside the string to avoid hotspot formation in the shaded PV modules. Therefore, the...

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Autores principales:	Ehab Mohamed Ali, Ahmed K. Abdelsalam, Karim H. Youssef, Ahmed A. Hossam-Eldin
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Cuckoo Search Algorithm (CSA) Global Maximum Power Point Tracking (GMPPT) partial shading (PS) photovoltaic (PV) Technology T
Acceso en línea:	https://doaj.org/article/ee99b124368b493f988561808b671679
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spelling	oai:doaj.org-article:ee99b124368b493f988561808b6716792021-11-11T15:58:54ZAn Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions10.3390/en142172101996-1073https://doaj.org/article/ee99b124368b493f988561808b6716792021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/21/7210https://doaj.org/toc/1996-1073The output power against voltage curve of the photovoltaic system changes its characteristics under partial shading conditions because of using bypass diodes. These bypass diodes are connected across the PV modules inside the string to avoid hotspot formation in the shaded PV modules. Therefore, the output curve has multiple power peaks with only one Global Max Power Point. The classical Maximum Power Point Tracking algorithms may fail to track that Global Max Power. Several soft computing algorithms have been proposed to improve tracking efficiency with different optimization principles. In this paper, an Improved Cuckoo Search Algorithm has been proposed to increase the tracking speed with minimum output power oscillation. The proposed algorithm avoids spreading the initial particles among the whole curve to predict shading pattern, but it reduces the exploration area after each iteration to compensate for the algorithm’s randomness. The proposed algorithm was compared with other methods by simulation using MATLAB/Simulink program and with practical experiments under the same operating conditions. The comparison showed that the proposed algorithm overcomes the other methods’ drawbacks and concurrently minimizes the convergence time, power oscillation, and system power losses.Ehab Mohamed AliAhmed K. AbdelsalamKarim H. YoussefAhmed A. Hossam-EldinMDPI AGarticleCuckoo Search Algorithm (CSA)Global Maximum Power Point Tracking (GMPPT)partial shading (PS)photovoltaic (PV)TechnologyTENEnergies, Vol 14, Iss 7210, p 7210 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Cuckoo Search Algorithm (CSA) Global Maximum Power Point Tracking (GMPPT) partial shading (PS) photovoltaic (PV) Technology T
spellingShingle	Cuckoo Search Algorithm (CSA) Global Maximum Power Point Tracking (GMPPT) partial shading (PS) photovoltaic (PV) Technology T Ehab Mohamed Ali Ahmed K. Abdelsalam Karim H. Youssef Ahmed A. Hossam-Eldin An Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions
description	The output power against voltage curve of the photovoltaic system changes its characteristics under partial shading conditions because of using bypass diodes. These bypass diodes are connected across the PV modules inside the string to avoid hotspot formation in the shaded PV modules. Therefore, the output curve has multiple power peaks with only one Global Max Power Point. The classical Maximum Power Point Tracking algorithms may fail to track that Global Max Power. Several soft computing algorithms have been proposed to improve tracking efficiency with different optimization principles. In this paper, an Improved Cuckoo Search Algorithm has been proposed to increase the tracking speed with minimum output power oscillation. The proposed algorithm avoids spreading the initial particles among the whole curve to predict shading pattern, but it reduces the exploration area after each iteration to compensate for the algorithm’s randomness. The proposed algorithm was compared with other methods by simulation using MATLAB/Simulink program and with practical experiments under the same operating conditions. The comparison showed that the proposed algorithm overcomes the other methods’ drawbacks and concurrently minimizes the convergence time, power oscillation, and system power losses.
format	article
author	Ehab Mohamed Ali Ahmed K. Abdelsalam Karim H. Youssef Ahmed A. Hossam-Eldin
author_facet	Ehab Mohamed Ali Ahmed K. Abdelsalam Karim H. Youssef Ahmed A. Hossam-Eldin
author_sort	Ehab Mohamed Ali
title	An Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions
title_short	An Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions
title_full	An Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions
title_fullStr	An Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions
title_full_unstemmed	An Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions
title_sort	enhanced cuckoo search algorithm fitting for photovoltaic systems’ global maximum power point tracking under partial shading conditions
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/ee99b124368b493f988561808b671679
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An Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions

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