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dc.contributor.authorFerreira, Luiz A. S.
dc.contributor.authorLoschi, Hermes J.
dc.contributor.authorRodriguez, Abel A. D.
dc.contributor.authorIano, Yuzo
dc.contributor.authordo Nascimento, Douglas A.
dc.date.accessioned2019-02-28T11:07:14Z
dc.date.available2019-02-28T11:07:14Z
dc.date.copyright2/20/2018 12:00:00 AM
dc.date.issued2018
dc.identifier.issn0199-6231
dc.identifier.othersol_140_02_021010.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4252892
dc.description.abstractThe performance of photovoltaic (PV) systems is highly influenced by the tilt angle of PV modules and the incidence of global solar irradiance, which may change the solar to electrical conversion efficiency. Some authors have addressed these uncertainties arising from PV solar generation by using mechanisms and methods in which solar tracking systems are integrated to PV systems. Since the advent of the internet of things (IoT), this solar tracking strategy has yet to meet the requirements of scalable distributed power systems that can seamlessly support the PV solar generation, mainly for remote monitoring and control. In this context, this paper aims at developing a prospective study devoted to examine fundamental concepts to implement solar tracking algorithms based on local solar time by using embedded technology from the IoT platform. Preliminary results evidenced an improvement of up to 38% in power generation performance for algorithm-driven PV modules compared to fixed PV modules.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleA Solar Tracking System Based on Local Solar Time Integrated to Photovoltaic Systems
dc.typeJournal Paper
dc.journal.volume140
dc.journal.issue2
dc.journal.titleJournal of Solar Energy Engineering
dc.identifier.doi10.1115/1.4039094
dc.journal.fristpage21010
dc.journal.lastpage021010-9
dc.treeJournal of Solar Energy Engineering:;2018:;volume( 140 ):;issue: 002
dc.contenttypeFulltext


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