A novel modified ant colony optimization based maximum power point tracking controller for photovoltaic systems

Phanden, Rakesh Kumar; Sharma, Lalit; Chhabra, Jatinder; Demir, Halil Ibrahim

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dc.date.accessioned	2021-06-04T08:06:07Z
dc.date.available	2021-06-04T08:06:07Z
dc.date.issued	2021
dc.identifier.issn	2214-7853
dc.identifier.uri	https://hdl.handle.net/20.500.12619/95635
dc.description	Bu yayının lisans anlaşması koşulları tam metin açık erişimine izin vermemektedir.
dc.description.abstract	Due to their versatility and local optima avoidance ability, meta-heuristic optimization techniques have been applied to various nonlinear engineering problems over the last decay. This paper presents a modified Ant Colony Optimization (ACO) Algorithm based controller for Maximum Power Point Tracking (MPPT) of a stand-alone photovoltaic (PV) system. ACO algorithm is modified to track the maximum power point with rapid pace and accuracy. MATLAB (R)/SIMULINK (R) environment is used for modelling of modified ACO based MPPT controller. Simulation results demonstrate the effectiveness of modified ACO based MPPT controller for MPPT tracking in standalone PV system performance. (C) 2020 Elsevier Ltd. All rights reserved.
dc.language	English
dc.language	İngilizce
dc.language.iso	eng
dc.publisher	ELSEVIER
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	A novel modified ant colony optimization based maximum power point tracking controller for photovoltaic systems
dc.type	Proceedings Paper
dc.identifier.volume	38
dc.identifier.startpage	89
dc.identifier.endpage	93
dc.relation.journal	MATERIALS TODAY-PROCEEDINGS
dc.identifier.wos	WOS:000621177500018
dc.identifier.doi	10.1016/j.matpr.2020.06.020
dc.contributor.author	Phanden, Rakesh Kumar
dc.contributor.author	Sharma, Lalit
dc.contributor.author	Chhabra, Jatinder
dc.contributor.author	Demir, Halil Ibrahim
dc.relation.publicationcategory	Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı