A novel energy saving system for office lighting control by using RBFNN and PSO

Wa Si, Harutoshi Ogai, Tansheng Li, Katsumi Hirai

研究成果: Conference contribution

7 引用 (Scopus)

抄録

This paper represents a novel energy saving system for office lighting control which consists of LED lamps, one illumination sensor for measuring the natural illumination condition, and one control module for the integrated control. The control module embeds an intelligent algorithm for generating the optimized dimming pattern according to the natural illumination and occupancy condition. The intelligent algorithm contains 1) Radial Basis Function Neural Networks (RBFNN) which are used to calculate the illuminance contribution from each luminaire to different positions in the office 2) a PSO algorithm which is used to optimize dimming ratio for luminaires according to the target illuminance in occupied areas thus provide optimized control strategy for the office. Simulations are made to prove the feasibility and effectiveness of the illumination simulator.

元の言語English
ホスト出版物のタイトルIEEE 2013 Tencon - Spring, TENCONSpring 2013 - Conference Proceedings
ページ347-351
ページ数5
DOI
出版物ステータスPublished - 2013
イベント2013 1st IEEE TENCON Spring Conference, TENCONSpring 2013 - Sydney, NSW
継続期間: 2013 4 172013 4 19

Other

Other2013 1st IEEE TENCON Spring Conference, TENCONSpring 2013
Sydney, NSW
期間13/4/1713/4/19

Fingerprint

Particle swarm optimization (PSO)
Energy conservation
Lighting
Neural networks
Dimming (lamps)
Lighting fixtures
Integrated control
Electric lamps
Light emitting diodes
Simulators
Sensors

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

これを引用

Si, W., Ogai, H., Li, T., & Hirai, K. (2013). A novel energy saving system for office lighting control by using RBFNN and PSO. : IEEE 2013 Tencon - Spring, TENCONSpring 2013 - Conference Proceedings (pp. 347-351). [6584469] https://doi.org/10.1109/TENCONSpring.2013.6584469

A novel energy saving system for office lighting control by using RBFNN and PSO. / Si, Wa; Ogai, Harutoshi; Li, Tansheng; Hirai, Katsumi.

IEEE 2013 Tencon - Spring, TENCONSpring 2013 - Conference Proceedings. 2013. p. 347-351 6584469.

研究成果: Conference contribution

Si, W, Ogai, H, Li, T & Hirai, K 2013, A novel energy saving system for office lighting control by using RBFNN and PSO. : IEEE 2013 Tencon - Spring, TENCONSpring 2013 - Conference Proceedings., 6584469, pp. 347-351, 2013 1st IEEE TENCON Spring Conference, TENCONSpring 2013, Sydney, NSW, 13/4/17. https://doi.org/10.1109/TENCONSpring.2013.6584469
Si W, Ogai H, Li T, Hirai K. A novel energy saving system for office lighting control by using RBFNN and PSO. : IEEE 2013 Tencon - Spring, TENCONSpring 2013 - Conference Proceedings. 2013. p. 347-351. 6584469 https://doi.org/10.1109/TENCONSpring.2013.6584469
Si, Wa ; Ogai, Harutoshi ; Li, Tansheng ; Hirai, Katsumi. / A novel energy saving system for office lighting control by using RBFNN and PSO. IEEE 2013 Tencon - Spring, TENCONSpring 2013 - Conference Proceedings. 2013. pp. 347-351
@inproceedings{c8961c549daa4a7eaccfd555549e4a5b,
title = "A novel energy saving system for office lighting control by using RBFNN and PSO",
abstract = "This paper represents a novel energy saving system for office lighting control which consists of LED lamps, one illumination sensor for measuring the natural illumination condition, and one control module for the integrated control. The control module embeds an intelligent algorithm for generating the optimized dimming pattern according to the natural illumination and occupancy condition. The intelligent algorithm contains 1) Radial Basis Function Neural Networks (RBFNN) which are used to calculate the illuminance contribution from each luminaire to different positions in the office 2) a PSO algorithm which is used to optimize dimming ratio for luminaires according to the target illuminance in occupied areas thus provide optimized control strategy for the office. Simulations are made to prove the feasibility and effectiveness of the illumination simulator.",
keywords = "Energy Saving System, Office Lighting, Particle Swarm Optimization, Radial Basis Function Neural Networks",
author = "Wa Si and Harutoshi Ogai and Tansheng Li and Katsumi Hirai",
year = "2013",
doi = "10.1109/TENCONSpring.2013.6584469",
language = "English",
isbn = "9781467363495",
pages = "347--351",
booktitle = "IEEE 2013 Tencon - Spring, TENCONSpring 2013 - Conference Proceedings",

}

TY - GEN

T1 - A novel energy saving system for office lighting control by using RBFNN and PSO

AU - Si, Wa

AU - Ogai, Harutoshi

AU - Li, Tansheng

AU - Hirai, Katsumi

PY - 2013

Y1 - 2013

N2 - This paper represents a novel energy saving system for office lighting control which consists of LED lamps, one illumination sensor for measuring the natural illumination condition, and one control module for the integrated control. The control module embeds an intelligent algorithm for generating the optimized dimming pattern according to the natural illumination and occupancy condition. The intelligent algorithm contains 1) Radial Basis Function Neural Networks (RBFNN) which are used to calculate the illuminance contribution from each luminaire to different positions in the office 2) a PSO algorithm which is used to optimize dimming ratio for luminaires according to the target illuminance in occupied areas thus provide optimized control strategy for the office. Simulations are made to prove the feasibility and effectiveness of the illumination simulator.

AB - This paper represents a novel energy saving system for office lighting control which consists of LED lamps, one illumination sensor for measuring the natural illumination condition, and one control module for the integrated control. The control module embeds an intelligent algorithm for generating the optimized dimming pattern according to the natural illumination and occupancy condition. The intelligent algorithm contains 1) Radial Basis Function Neural Networks (RBFNN) which are used to calculate the illuminance contribution from each luminaire to different positions in the office 2) a PSO algorithm which is used to optimize dimming ratio for luminaires according to the target illuminance in occupied areas thus provide optimized control strategy for the office. Simulations are made to prove the feasibility and effectiveness of the illumination simulator.

KW - Energy Saving System

KW - Office Lighting

KW - Particle Swarm Optimization

KW - Radial Basis Function Neural Networks

UR - http://www.scopus.com/inward/record.url?scp=84883664708&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84883664708&partnerID=8YFLogxK

U2 - 10.1109/TENCONSpring.2013.6584469

DO - 10.1109/TENCONSpring.2013.6584469

M3 - Conference contribution

AN - SCOPUS:84883664708

SN - 9781467363495

SP - 347

EP - 351

BT - IEEE 2013 Tencon - Spring, TENCONSpring 2013 - Conference Proceedings

ER -