Please use this identifier to cite or link to this item: http://dspace2020.uniten.edu.my:8080/handle/123456789/10508
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dc.contributor.authorKumar, K.en_US
dc.contributor.authorTiwari, R.en_US
dc.contributor.authorBabu, N.R.en_US
dc.contributor.authorPadmanaban, S.en_US
dc.contributor.authorBhaskar, M.S.en_US
dc.contributor.authorRamachandaramurthy, V.K.en_US
dc.date.accessioned2018-11-07T08:11:25Z-
dc.date.available2018-11-07T08:11:25Z-
dc.date.issued2018-
dc.description.abstractA hybrid high voltage-gain DC-DC power converter is presented to the renewable photovoltaic (PV) application. The extraction of maximum power and power electronics conversion from small voltage Renewable Energy Sources (RES) to a required voltage level is the main function of DC-DC converters. The traditional Boost and self lift Cuk converters are hybridized by sharing single switch, for obtaining the high voltage gain. The artificial neural network based MPPT is considered to take out extreme power from the Renewable Energy Sources (RES). The proposed hybrid DC-DC converter is compared to the hybrid Boost and Cuk converter along with the MPPT technique. Simulation outcome is presented to verify the concept of the proposed converter. © 2017 IEEE.
dc.language.isoenen_US
dc.titleAnalysis of high voltage-gain hybrid DC-DC power converter with RBFN based MPPT for renewable photovoltaic applicationsen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/CENCON.2017.8262501-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.openairetypeArticle-
Appears in Collections:COE Scholarly Publication
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