Please use this identifier to cite or link to this item:
http://dspace.uniten.edu.my/jspui/handle/123456789/11604
DC Field | Value | Language |
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dc.contributor.author | Iman, M.I. | en_US |
dc.contributor.author | Roslan, M.F. | en_US |
dc.contributor.author | Ker, P.J. | en_US |
dc.contributor.author | Hannan, M.A. | en_US |
dc.date.accessioned | 2019-01-16T08:41:45Z | - |
dc.date.available | 2019-01-16T08:41:45Z | - |
dc.date.issued | 2018 | - |
dc.description.abstract | 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. | en_US |
dc.language.iso | en | en_US |
dc.title | An intelligent maximum power point tracking algorithm for Photovoltaic System | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.14419/ijet.v7i4.35.22861 | - |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
Appears in Collections: | UNITEN Scholarly Publication |
Files in This Item:
File | Size | Format | |
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An intelligent maximum power point tracking algorithm for Photovoltaic System.pdf | 999.56 kB | Adobe PDF | View/Open |
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