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 of the...
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2018-07-01.
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| LEADER | 03099 am a22003013u 4500 | ||
|---|---|---|---|
| 001 | ijeecs12766_8661 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Wagiman, Khairul Rijal |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Abdullah, Mohd Noor |e author |
| 245 | 0 | 0 | |a Intelligent Lighting Control System for Energy Savings in Office Building |
| 260 | |b Institute of Advanced Engineering and Science, |c 2018-07-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/12766 | ||
| 520 | |a 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%.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%. | ||
| 540 | |a Copyright (c) 2018 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
| 546 | |a eng | ||
| 690 | |||
| 690 | |a artificial neural network; energy savings; lighting control system; lighting retrofit | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 11, No 1: July 2018; 195-202 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v11.i1 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/12766/8661 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/12766/8661 |z Get fulltext |