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An intelligent maximum power point tracking algorithm for Photovoltaic System

This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. A PV panel, DC-DC Boost converter and resistive load was utiliz...

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Main Authors: Iman M.I., Roslan M.F., Ker P.J., Hannan M.A.
Other Authors: 57205235742
Format: Article
Published: Science Publishing Corporation Inc 2023
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spelling my.uniten.dspace-240152023-05-29T14:54:20Z An intelligent maximum power point tracking algorithm for Photovoltaic System Iman M.I. Roslan M.F. Ker P.J. Hannan M.A. 57205235742 57220188085 37461740800 7103014445 This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. A PV panel, DC-DC Boost converter and resistive load was utilized as PV system. Three different MPPT algorithms were implemented in the converter. The result obtained from the converter was analyzed and compared to find the best algorithm to be used to identify the point in which maximum power can be achieve in a PV system. The objective is to reduce the time taken for the tracking of maximum power point of PV application system and minimize output power oscillation. The simulation was done by using MATLAB/Simulink with DC-DC Boost converter. The result shows that FLC method with PSO has achieved the fastest response time to track MPP and provide minimum oscillation compared to conventional P & O and FLC techniques. � 2018 Authors. Final 2023-05-29T06:54:19Z 2023-05-29T06:54:19Z 2018 Article 10.14419/ijet.v7i4.35.22861 2-s2.0-85059242034 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059242034&doi=10.14419%2fijet.v7i4.35.22861&partnerID=40&md5=67542bb090f2d4efb879a50433e751f9 https://irepository.uniten.edu.my/handle/123456789/24015 7 4 457 462 Science Publishing Corporation Inc Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. A PV panel, DC-DC Boost converter and resistive load was utilized as PV system. Three different MPPT algorithms were implemented in the converter. The result obtained from the converter was analyzed and compared to find the best algorithm to be used to identify the point in which maximum power can be achieve in a PV system. The objective is to reduce the time taken for the tracking of maximum power point of PV application system and minimize output power oscillation. The simulation was done by using MATLAB/Simulink with DC-DC Boost converter. The result shows that FLC method with PSO has achieved the fastest response time to track MPP and provide minimum oscillation compared to conventional P & O and FLC techniques. � 2018 Authors.
author2 57205235742
author_facet 57205235742
Iman M.I.
Roslan M.F.
Ker P.J.
Hannan M.A.
format Article
author Iman M.I.
Roslan M.F.
Ker P.J.
Hannan M.A.
spellingShingle Iman M.I.
Roslan M.F.
Ker P.J.
Hannan M.A.
An intelligent maximum power point tracking algorithm for Photovoltaic System
author_sort Iman M.I.
title An intelligent maximum power point tracking algorithm for Photovoltaic System
title_short An intelligent maximum power point tracking algorithm for Photovoltaic System
title_full An intelligent maximum power point tracking algorithm for Photovoltaic System
title_fullStr An intelligent maximum power point tracking algorithm for Photovoltaic System
title_full_unstemmed An intelligent maximum power point tracking algorithm for Photovoltaic System
title_sort intelligent maximum power point tracking algorithm for photovoltaic system
publisher Science Publishing Corporation Inc
publishDate 2023
_version_ 1806455104843284480
score 13.211869

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