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An improved maximum power point tracking controller for PV systems using artificial neural network; [Ulepszona metoda ?ledzenia maksymalnej mocy systemu fotowoltaicznego z wykorzystaniem sieci neuronowej]

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dc.citedby43
dc.contributor.authorYounis M.A.en_US
dc.contributor.authorKhatib T.en_US
dc.contributor.authorNajeeb M.en_US
dc.contributor.authorMohd Ariffin A.en_US
dc.contributor.authorid56501517900en_US
dc.contributor.authorid31767521400en_US
dc.contributor.authorid55052092300en_US
dc.contributor.authorid16400722400en_US
dc.date.accessioned2023-12-28T06:30:20Z
dc.date.available2023-12-28T06:30:20Z
dc.date.issued2012
dc.description.abstractThis paper presents an improved maximum power point tracking (MPPT) controller for PV systems. An Artificial Neural Network and the classical P&O algorithm were employed to achieve this objective. MATLAB models for a neural network, PV module, and the classical P&O algorithm are developed. However, the developed MPPT uses the ANN to predict the optimum voltage of the PV system in order to extract the maximum power point (MPP). The developed ANN has a feedback propagation configuration and it has four inputs which are solar radiation, ambient temperature, and the temperature coefficients of Isc and Voc of the modeled PV module. Meanwhile, the optimum voltage of the PV system is the output of the developed ANN. Based on the results; the response of the proposed MPPT controller is faster than the classical P&O algorithm. Moreover, the average tracking efficiency of the developed algorithm was 95.51% as compared to 85.99% of the classical P&O algorithm. Such developed controller increases the conversion efficiency of a PV system.en_US
dc.description.natureFinalen_US
dc.identifier.epage121
dc.identifier.issue3 B
dc.identifier.scopus2-s2.0-84857755382
dc.identifier.spage116
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84857755382&partnerID=40&md5=d84e0303b0536b5ac8640afab1e4c3d5
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29522
dc.identifier.volume88
dc.pagecount5
dc.sourceScopus
dc.sourcetitlePrzeglad Elektrotechniczny
dc.subjectANN
dc.subjectMPPT
dc.subjectP and O algorithm
dc.subjectPV systems
dc.titleAn improved maximum power point tracking controller for PV systems using artificial neural network; [Ulepszona metoda ?ledzenia maksymalnej mocy systemu fotowoltaicznego z wykorzystaniem sieci neuronowej]en_US
dc.typeArticleen_US
dspace.entity.typePublication
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