Intelligent lighting control system for energy savings in office building

Lighting system is a crucial sub-system and consumes substantial electricity energy in the buildings. This paper proposes an intelligent lighting control system using artificial neural network (ANN). The minimization of dimming levels of luminaires has been considered as an objective function o...

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Main Authors: Wagiman, Khairul Rijal, Abdullah, Mohd Noor
Format: Article
Language:English
Published: 2018
Subjects:
Online Access:http://eprints.uthm.edu.my/7200/
http://eprints.uthm.edu.my/7200/1/J14060_76d5c75f2cfc2c63c2df4ebb9b1970f3.pdf
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author Wagiman, Khairul Rijal
Abdullah, Mohd Noor
author_facet Wagiman, Khairul Rijal
Abdullah, Mohd Noor
author_sort Wagiman, Khairul Rijal
building UTHM Institutional Repository
collection Online Access
description Lighting system is a crucial sub-system and consumes substantial electricity energy in the buildings. This paper proposes an intelligent lighting control system using artificial neural network (ANN). The minimization of dimming levels of luminaires has been considered as an objective function of the controller. Moreover, the light sensor field of view is also taken into consideration in objective function formulation. The proposed ANN controller has been tested on an actual office room of the Department of Mechanical Technology, Institute of Industrial Training, Selandar, Melaka, Malaysia. The simulation has been carried out using DIALux simulation lighting software. Based on the results, the proposed controller showed great performance in terms of adaptive less light sensor data and achieving dimming levels target that complies the European Standard EN12464-1. Furthermore, it can save energy up to 34%.
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spelling uthm-72002022-06-21T02:07:13Z http://eprints.uthm.edu.my/7200/ Intelligent lighting control system for energy savings in office building Wagiman, Khairul Rijal Abdullah, Mohd Noor TK4125-4399 Electric lighting Lighting system is a crucial sub-system and consumes substantial electricity energy in the buildings. This paper proposes an intelligent lighting control system using artificial neural network (ANN). The minimization of dimming levels of luminaires has been considered as an objective function of the controller. Moreover, the light sensor field of view is also taken into consideration in objective function formulation. The proposed ANN controller has been tested on an actual office room of the Department of Mechanical Technology, Institute of Industrial Training, Selandar, Melaka, Malaysia. The simulation has been carried out using DIALux simulation lighting software. Based on the results, the proposed controller showed great performance in terms of adaptive less light sensor data and achieving dimming levels target that complies the European Standard EN12464-1. Furthermore, it can save energy up to 34%. 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/7200/1/J14060_76d5c75f2cfc2c63c2df4ebb9b1970f3.pdf Wagiman, Khairul Rijal and Abdullah, Mohd Noor (2018) Intelligent lighting control system for energy savings in office building. Indonesian Journal of Electrical Engineering and Computer Science, 11 (1). pp. 195-202. ISSN 2502-4752 https://doi.org/10.11591/ijeecs.v11.i1.pp195-202
spellingShingle TK4125-4399 Electric lighting
Wagiman, Khairul Rijal
Abdullah, Mohd Noor
Intelligent lighting control system for energy savings in office building
title Intelligent lighting control system for energy savings in office building
title_full Intelligent lighting control system for energy savings in office building
title_fullStr Intelligent lighting control system for energy savings in office building
title_full_unstemmed Intelligent lighting control system for energy savings in office building
title_short Intelligent lighting control system for energy savings in office building
title_sort intelligent lighting control system for energy savings in office building
topic TK4125-4399 Electric lighting
url http://eprints.uthm.edu.my/7200/
http://eprints.uthm.edu.my/7200/
http://eprints.uthm.edu.my/7200/1/J14060_76d5c75f2cfc2c63c2df4ebb9b1970f3.pdf