A comprehensive review of maximum power point tracking algorithms for photovoltaic systems

In recent decades, Photovoltaic (PV) energy has made significant progress towards meeting the continuously increasing world energy demand. Besides that, the issue of conventional fossil fuels depletion as well as environmental pollution both contribute to the growth of PV technology. However, the de...

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書目詳細資料
發表在:Renewable and Sustainable Energy Reviews
主要作者: 2-s2.0-84902194752
格式: Review
語言:English
出版: Elsevier Ltd 2014
在線閱讀:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902194752&doi=10.1016%2fj.rser.2014.05.045&partnerID=40&md5=dd5944a02f6e356cb5738876a6b0c9cf
id Kamarzaman N.A.; Tan C.W.
spelling Kamarzaman N.A.; Tan C.W.
2-s2.0-84902194752
A comprehensive review of maximum power point tracking algorithms for photovoltaic systems
2014
Renewable and Sustainable Energy Reviews
37

10.1016/j.rser.2014.05.045
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902194752&doi=10.1016%2fj.rser.2014.05.045&partnerID=40&md5=dd5944a02f6e356cb5738876a6b0c9cf
In recent decades, Photovoltaic (PV) energy has made significant progress towards meeting the continuously increasing world energy demand. Besides that, the issue of conventional fossil fuels depletion as well as environmental pollution both contribute to the growth of PV technology. However, the deployment and implementation of photovoltaic systems remain as a great challenge, since the PV material cost is still very high. The low PV module conversion efficiency is another factor that restricts the wide usage of PV systems, therefore a power converter embedded with the capability of maximum power point tracking (MPPT) integrated with PV systems is essential to further the technology. This paper provides a comprehensive review of the available MPPT techniques, both the uniform insolation and partial shaded conditions. In order to appreciate the knowledge of MPPT concepts, several types of PV cell equivalent models are explained too. Conventional MPPT techniques have proven the ability to track the maximum power point (MPP) under uniform solar irradiance. However, under rapidly changing environments and partially shaded conditions, conventional techniques have failed to track the true MPP. For this reason, stochastic based methods and artificial intelligence have been developed with the ability to seek the true MPP under multiple peaks with good convergence speed. This paper analyses and compares both conventional and stochastic MPPT techniques based on the true MPP tracking capability, design complexity, cost consideration, sensitivity to environmental change and convergence speed. Comparatively, the stochastic algorithms and artificial intelligence show excellent tracking performance. The research on MPPT techniques is ongoing towards achieving a better performance in terms of the ease of implementation, low system cost and better tracking efficiency. © 2014 Elsevier Ltd.
Elsevier Ltd
13640321
English
Review

author 2-s2.0-84902194752
spellingShingle 2-s2.0-84902194752
A comprehensive review of maximum power point tracking algorithms for photovoltaic systems
author_facet 2-s2.0-84902194752
author_sort 2-s2.0-84902194752
title A comprehensive review of maximum power point tracking algorithms for photovoltaic systems
title_short A comprehensive review of maximum power point tracking algorithms for photovoltaic systems
title_full A comprehensive review of maximum power point tracking algorithms for photovoltaic systems
title_fullStr A comprehensive review of maximum power point tracking algorithms for photovoltaic systems
title_full_unstemmed A comprehensive review of maximum power point tracking algorithms for photovoltaic systems
title_sort A comprehensive review of maximum power point tracking algorithms for photovoltaic systems
publishDate 2014
container_title Renewable and Sustainable Energy Reviews
container_volume 37
container_issue
doi_str_mv 10.1016/j.rser.2014.05.045
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902194752&doi=10.1016%2fj.rser.2014.05.045&partnerID=40&md5=dd5944a02f6e356cb5738876a6b0c9cf
description In recent decades, Photovoltaic (PV) energy has made significant progress towards meeting the continuously increasing world energy demand. Besides that, the issue of conventional fossil fuels depletion as well as environmental pollution both contribute to the growth of PV technology. However, the deployment and implementation of photovoltaic systems remain as a great challenge, since the PV material cost is still very high. The low PV module conversion efficiency is another factor that restricts the wide usage of PV systems, therefore a power converter embedded with the capability of maximum power point tracking (MPPT) integrated with PV systems is essential to further the technology. This paper provides a comprehensive review of the available MPPT techniques, both the uniform insolation and partial shaded conditions. In order to appreciate the knowledge of MPPT concepts, several types of PV cell equivalent models are explained too. Conventional MPPT techniques have proven the ability to track the maximum power point (MPP) under uniform solar irradiance. However, under rapidly changing environments and partially shaded conditions, conventional techniques have failed to track the true MPP. For this reason, stochastic based methods and artificial intelligence have been developed with the ability to seek the true MPP under multiple peaks with good convergence speed. This paper analyses and compares both conventional and stochastic MPPT techniques based on the true MPP tracking capability, design complexity, cost consideration, sensitivity to environmental change and convergence speed. Comparatively, the stochastic algorithms and artificial intelligence show excellent tracking performance. The research on MPPT techniques is ongoing towards achieving a better performance in terms of the ease of implementation, low system cost and better tracking efficiency. © 2014 Elsevier Ltd.
publisher Elsevier Ltd
issn 13640321
language English
format Review
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record_format scopus
collection Scopus
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