Publication:
Optimization variation for multiple heuristic approaches in solar tracking

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dc.citedby1
dc.contributor.authorFam D.F.en_US
dc.contributor.authorKoh S.P.en_US
dc.contributor.authorTiong S.K.en_US
dc.contributor.authorChong K.H.en_US
dc.contributor.authorid43361142100en_US
dc.contributor.authorid22951210700en_US
dc.contributor.authorid15128307800en_US
dc.contributor.authorid36994481200en_US
dc.date.accessioned2023-12-28T07:05:39Z
dc.date.available2023-12-28T07:05:39Z
dc.date.issued2011
dc.description.abstractThe solar tracker, a device that keeps PV or photo-thermal panels in an optimum position perpendicular to the solar radiation during daylight hours, increases the collected energy and can be considered as one of the economical renewable energy in generating electricity. The current trend in solar concentrator tracking system is to use an open-loop local controller that computes the direction of the solar vector based on geographical location and time. It is not accurate because it has error from computing the intensity variation. Literature suggested that the photovoltaic panels could produce maximum power if the panels have angle of inclination zero degree to the sun position. In this research, genetic algorithm is one of the optimization techniques used to maximize the performance of solar tracking system. Research shows that among the heuristic approaches within 50 generation, Genetic Algorithm reaches the best fitness value at 0.01706 with optimum voltage 10.05V. � (2011) Trans Tech Publications, Switzerland.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.4028/www.scientific.net/KEM.480-481.1085
dc.identifier.epage1090
dc.identifier.scopus2-s2.0-79960444969
dc.identifier.spage1085
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-79960444969&doi=10.4028%2fwww.scientific.net%2fKEM.480-481.1085&partnerID=40&md5=348c068e2c0ad05379af74dde74ee80b
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29561
dc.identifier.volume480-481
dc.pagecount5
dc.publisherTrans Tech Publications Ltden_US
dc.sourceScopus
dc.sourcetitleKey Engineering Materials
dc.subjectGenetic algorithm
dc.subjectSimulated annealing
dc.subjectSolar tracking
dc.subjectThreshold acceptance
dc.subjectGenetic algorithms
dc.subjectHeuristic methods
dc.subjectPhotovoltaic cells
dc.subjectSimulated annealing
dc.subjectTracking (position)
dc.subjectGeographical locations
dc.subjectHeuristic approach
dc.subjectIntensity variations
dc.subjectOptimization techniques
dc.subjectPhotovoltaic panels
dc.subjectSolar tracking
dc.subjectSolar tracking systems
dc.subjectThreshold acceptances
dc.subjectSolar power generation
dc.titleOptimization variation for multiple heuristic approaches in solar trackingen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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