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Evaluation of genetic algorithm based solar tracking system for photovoltaic panels

The maximum power supplied by a photovoltaic (PV) panels system change over time. It depends on environmental factors such as the solar irradiation and the temperature of these panels. The average solar energy harvested by the conventional solar panels during the course of the day, is not always max...

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Main Authors: Mashohor, Syamsiah, Samsudin, Khairulmizam, M. Noor, Amirullah, A. Rahman, Adi Razlan
Format: Conference or Workshop Item
Language:English
Published: IEEE 2008
Online Access:http://psasir.upm.edu.my/id/eprint/48081/1/Evaluation%20of%20genetic%20algorithm%20based%20solar%20tracking%20system%20for%20photovoltaic%20panels.pdf
http://psasir.upm.edu.my/id/eprint/48081/
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spelling my.upm.eprints.480812016-08-03T07:54:43Z http://psasir.upm.edu.my/id/eprint/48081/ Evaluation of genetic algorithm based solar tracking system for photovoltaic panels Mashohor, Syamsiah Samsudin, Khairulmizam M. Noor, Amirullah A. Rahman, Adi Razlan The maximum power supplied by a photovoltaic (PV) panels system change over time. It depends on environmental factors such as the solar irradiation and the temperature of these panels. The average solar energy harvested by the conventional solar panels during the course of the day, is not always maximized. This is due to the static placement of the panel which limits their area of exposure to the sun. In practice, there are three possible approaches for maximizing the solar power extraction in medium and large scale PV systems are sun tracking, maximum power point (MPP) tracking or combination of both. In this paper, a genetic algorithm (GA) has been proposed utilizing sun tracking approaches to maximize the performance of PV panels. Literature suggested that the PV panels could produce maximum power if the panels have angle of inclination zero degree to the sun position. This work evaluate the best combination of GA parameters to optimize a solar tracking system for PV panels in terms of azimuth angle and tilt angle. Simulation results demonstrated the ability of the proposed GA system to search for optimal panel positions in term of consistency and convergence properties. It also has proved the ability of the GA-solar to adapt to different environmental conditions and successfully track sun positions in finding the maximum power by precisely orienting the PV panels. IEEE 2008 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/48081/1/Evaluation%20of%20genetic%20algorithm%20based%20solar%20tracking%20system%20for%20photovoltaic%20panels.pdf Mashohor, Syamsiah and Samsudin, Khairulmizam and M. Noor, Amirullah and A. Rahman, Adi Razlan (2008) Evaluation of genetic algorithm based solar tracking system for photovoltaic panels. In: 2008 IEEE International Conference on Sustainable Energy Technologies (ICSET 2008), 24-27 Nov. 2008, Singapore. (pp. 269-273). 10.1109/ICSET.2008.4747015
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The maximum power supplied by a photovoltaic (PV) panels system change over time. It depends on environmental factors such as the solar irradiation and the temperature of these panels. The average solar energy harvested by the conventional solar panels during the course of the day, is not always maximized. This is due to the static placement of the panel which limits their area of exposure to the sun. In practice, there are three possible approaches for maximizing the solar power extraction in medium and large scale PV systems are sun tracking, maximum power point (MPP) tracking or combination of both. In this paper, a genetic algorithm (GA) has been proposed utilizing sun tracking approaches to maximize the performance of PV panels. Literature suggested that the PV panels could produce maximum power if the panels have angle of inclination zero degree to the sun position. This work evaluate the best combination of GA parameters to optimize a solar tracking system for PV panels in terms of azimuth angle and tilt angle. Simulation results demonstrated the ability of the proposed GA system to search for optimal panel positions in term of consistency and convergence properties. It also has proved the ability of the GA-solar to adapt to different environmental conditions and successfully track sun positions in finding the maximum power by precisely orienting the PV panels.
format Conference or Workshop Item
author Mashohor, Syamsiah
Samsudin, Khairulmizam
M. Noor, Amirullah
A. Rahman, Adi Razlan
spellingShingle Mashohor, Syamsiah
Samsudin, Khairulmizam
M. Noor, Amirullah
A. Rahman, Adi Razlan
Evaluation of genetic algorithm based solar tracking system for photovoltaic panels
author_facet Mashohor, Syamsiah
Samsudin, Khairulmizam
M. Noor, Amirullah
A. Rahman, Adi Razlan
author_sort Mashohor, Syamsiah
title Evaluation of genetic algorithm based solar tracking system for photovoltaic panels
title_short Evaluation of genetic algorithm based solar tracking system for photovoltaic panels
title_full Evaluation of genetic algorithm based solar tracking system for photovoltaic panels
title_fullStr Evaluation of genetic algorithm based solar tracking system for photovoltaic panels
title_full_unstemmed Evaluation of genetic algorithm based solar tracking system for photovoltaic panels
title_sort evaluation of genetic algorithm based solar tracking system for photovoltaic panels
publisher IEEE
publishDate 2008
url http://psasir.upm.edu.my/id/eprint/48081/1/Evaluation%20of%20genetic%20algorithm%20based%20solar%20tracking%20system%20for%20photovoltaic%20panels.pdf
http://psasir.upm.edu.my/id/eprint/48081/
_version_ 1643834068717010944
score 13.211869

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