Optimization variation for multiple heuristic approaches in solar tracking
The 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 co...
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my.uniten.dspace-295612023-12-28T15:05:39Z Optimization variation for multiple heuristic approaches in solar tracking Fam D.F. Koh S.P. Tiong S.K. Chong K.H. 43361142100 22951210700 15128307800 36994481200 Genetic algorithm Simulated annealing Solar tracking Threshold acceptance Genetic algorithms Heuristic methods Photovoltaic cells Simulated annealing Tracking (position) Geographical locations Heuristic approach Intensity variations Optimization techniques Photovoltaic panels Solar tracking Solar tracking systems Threshold acceptances Solar power generation The 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. Final 2023-12-28T07:05:39Z 2023-12-28T07:05:39Z 2011 Conference paper 10.4028/www.scientific.net/KEM.480-481.1085 2-s2.0-79960444969 https://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 https://irepository.uniten.edu.my/handle/123456789/29561 480-481 1085 1090 Trans Tech Publications Ltd Scopus |
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Genetic algorithm Simulated annealing Solar tracking Threshold acceptance Genetic algorithms Heuristic methods Photovoltaic cells Simulated annealing Tracking (position) Geographical locations Heuristic approach Intensity variations Optimization techniques Photovoltaic panels Solar tracking Solar tracking systems Threshold acceptances Solar power generation |
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Genetic algorithm Simulated annealing Solar tracking Threshold acceptance Genetic algorithms Heuristic methods Photovoltaic cells Simulated annealing Tracking (position) Geographical locations Heuristic approach Intensity variations Optimization techniques Photovoltaic panels Solar tracking Solar tracking systems Threshold acceptances Solar power generation Fam D.F. Koh S.P. Tiong S.K. Chong K.H. Optimization variation for multiple heuristic approaches in solar tracking |
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The 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. |
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43361142100 |
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43361142100 Fam D.F. Koh S.P. Tiong S.K. Chong K.H. |
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Conference paper |
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Fam D.F. Koh S.P. Tiong S.K. Chong K.H. |
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Fam D.F. |
title |
Optimization variation for multiple heuristic approaches in solar tracking |
title_short |
Optimization variation for multiple heuristic approaches in solar tracking |
title_full |
Optimization variation for multiple heuristic approaches in solar tracking |
title_fullStr |
Optimization variation for multiple heuristic approaches in solar tracking |
title_full_unstemmed |
Optimization variation for multiple heuristic approaches in solar tracking |
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optimization variation for multiple heuristic approaches in solar tracking |
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Trans Tech Publications Ltd |
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2023 |
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