THERMAL SCIENCE

International Scientific Journal

CONTROL OF THE LIGHTING SYSTEM USING A GENETIC ALGORITHM

ABSTRACT
The manufacturing, distribution and use of electricity are of fundamental importance for the social life and they have the biggest influence on the environment associated with any human activity. The energy needed for building lighting makes up 20-40% of the total consumption. This paper displays the development of the mathematical model and genetic algorithm for the control of dimmable lighting on problems of regulating the level of internal lighting and increase of energetic efficiency using daylight. A series of experiments using the optimization algorithm on the realized model confirmed very high savings in electricity consumption.
KEYWORDS
PAPER SUBMITTED: 2012-02-03
PAPER REVISED: 2012-03-02
PAPER ACCEPTED: 2012-03-13
DOI REFERENCE: https://doi.org/10.2298/TSCI120203075C
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2012, VOLUME 16, ISSUE Supplement 1, PAGES [S237 - S250]
REFERENCES
  1. ec.europa.eu/energy/publications/statistics/statistics_en.htm
  2. ec.europa.eu/energy/efficiency/buildings/buildings_en.htm
  3. www.eia.doe.gov/emeu/aer/consump.html
  4. Boyce, P., Hunter, C., Howlett, O., The benefits of daylight through windows, Lighting Research Center: Rensselaer Polytechnic Institute, New York, 2003
  5. Heschong, L., Daylighting and human performace, ASHRAE Journal, 44, 2002, pp. 65-67
  6. Plympton, P., Conway, S., Epstein, K., Daylighting in schools: improving student performance and health at a price schools can afford, NREL report CP-550-28059, National Renewable Energy Laboratory, Golden, CO, 2000
  7. BRE energy consumption guide 19, 1997
  8. Guide F. Energy effciency in buildings. Chartered Institute of Building Services Engineers, 1999
  9. Krarti, M., Energy audit of building systems: an engineering approach, Boca Raton, FL, CRC Press, 2000
  10. Hanselaer, P. et al., Power density targets for efficient lighting of interior task areas, Lighting Research and Technology, 39 (2007), 2 pp. 171-184
  11. Ryckaert, W., et al. Power density targets for efficient lighting: practical examples, Proceedings, Improving Energy Efficiency in Commercial Buildings Conference (IEECB), Frankfurt am Main, Germany, 2008, p. 9
  12. Waide, P., Tanishima, S., Light's Labour's Lost: Policies for Energy Efficient Lighting, OECD/IEA, Paris, 2006
  13. Doulos, L., Tsangrassoulis, A., Topalis, F., Quantifying energy savings in daylight responsive systems: the role of dimming electronic ballasts, Energy and Buildings, 40 (2008), pp. 36-50
  14. Li, D. H. W., Lam, T. N. T., Wong, S. L., Lighting and energy performance for an office using high frequency dimming controls, Energy Conversion and Management, 47 (2006), pp. 1133-1145
  15. Lee, E., Selkowitz, S., The New York times headquarters daylighting mockup: monitored performance, Energy and Buildings, 38 (2006), pp. 914-929
  16. Onaygil, S., Guler, O., Determination of the energy saving by daylight responsive lighting control system with an example from Istanbul, Building and Environment, 38 (2003), pp. 973-977
  17. Li, D. H. W., Lam, J., Wong, S., Daylighting and its implications to overall thermal transfer value (OTTV) determinations, Energy, 27 (2002), 11, pp. 991-1008
  18. Li, D.H.W., Lam, J., Wong, S., Daylighting and its effects on peak load determination, Energy, 30 (2005), 10, pp. 1817-1831
  19. Yener, A., A method of obtaining visual comfort using fixed shading devices in rooms, Building and Environment, 34 (1999), pp. 285-291
  20. The MathWorks Inc. Genetic Algorithm and Direct Search Toolbox - Users's Guide, www.mathworks.com, 2008
  21. Vas, P., Artificial Inteligence Based Electrical Machines and Drives, University of Aberdeen, Oxford University Press, 1999
  22. Man, K. F., Tang, K. S., Kwong, S., Genetic algorithms, Springer - Verlag, London, Great Britain, 1999
  23. Holtz, J., Sensorless Control of Induction Motor Drives, Proceedings of the IEEE, Vol. 90, 2002, pp. 1359-1394
  24. Whitley, D., A genetic algorithm tutorial, Statistics and Computing, vol. 4, pp. 65-85, 1994
  25. John, R., et al., Glazing energy performance and design optimization with daylighting. LBL-15625. USA: Lawrence Berkeley Laboratory, University of California, 1984
  26. www.thornlighting.com/com/en/res_calculation_progams_25951.htm
  27. Ferentinos, K.P., Albright, L.D., Optimal design of plant lighting system by genetic algorithms, Engineering Applications of Artificial Intelligence, 18 (2005), pp. 473-484
  28. Tregenza, P., et al., Daylight coefficients, Lighting Research and Technology, 15, (1983), 2, pp. 65-71
  29. Soler, A., Robledo, L. Investigation of the overcast skies luminance distribution using 35 sensors fixed on a dome, Energy Conversion and Management, 46 (2005), pp. 2739-2747
  30. CIE, S 011/E. Spatial distribution of daylight - CIE standard general sky, Standard, CIE Central Bureau, Vienna; 2003
  31. Li, D. H. W., Lau, C. C. S., Lam, J. C. Predicting daylight illuminance by computer simulation techniques, Lighting Research and Technology, 36 (2004), 2, pp. 113-129
  32. De Rosa, A. et al., INLUX: A calculation code for daylight illuminance predictions inside buildings and its experimental validation, Building and Environment, 44 (2009), pp. 1769-1775
  33. Li, D. H. W., Tsang, E. K. W. , An analysis of daylighting performance for office buildings in Hong Kong, Building and Environment, 43 (2008), pp. 1446-1458
  34. Li, D.H.W., Daylight and energy implications for CIE standard skies, Energy Conversion and Management, 2007
  35. Aizlewood, M., Littlefair, P., Daylight prediction methods: a survey of their use, Proceedings, CIBSE national lighting conference, Bath, UK, 1996, pp. 126-140
  36. Fergus, N., Wilson, M., Chiancarella, C., Using field measurements of desktop illuminance in European offices to investigate its dependence on outdoor conditions and its effect on occupant satisfaction, and the use of lights and blinds, Energy and Buildings, 38 (2006), pp. 802-813
  37. Kwang-Wook, P., Athienitis, A., Workplane illuminance prediction method for daylighting control systems, Solar Energy,75 (2003), pp. 277-284
  38. Kazanasma, T., Gunaydin, M., Binol, S., Artificial neural networks to predict daylight illuminance in office buildings, Building and Environment, 44 (2009), pp. 1751-1757
  39. Danny, H., Li, W., Wong, S. L., Daylighting and energy implications due to shading effects from nearby buildings, Applied Energy, 84 (2007), pp. 1199-1209
  40. CIBSE/SLL, Code for Lighting, Chartered Institution of Building Services Engineers/Society of Light and Lighting, London, 2002
  41. CEN, European Standard EN12464, Lighting of Workplaces, European Committee for Standardization, Brussels, 2003
  42. Jennings, J.D., et al., Comparison of control options in private offices in an advanced lighting controls testbed, Journal of the Illuminating Engineering Society (2000)
  43. Joakim, W., Annica, M., Nilsson, Ewa W., A combined Markov-chain and bottom-up approach to modelling of domestic lighting demand, Energy and Buildings, 41 (2009), pp. 1001-1012
  44. Roisin, B., et al., Lighting energy savings in offices using different control systems and their real consumption, Energy and Buildings, 40 (2008), pp. 514-523
  45. Guillemin, A., Morel, N., An innovative lighting controller integrated in a self-adaptive building control system, Energy and Buildings, 33 (2001), pp. 477-487
  46. Pino, A., et al., Thermal and lighting behavior of office buildings in Santiago of Chile, Energy and Buildings, 47 (2012), pp. 441-449
  47. Young Yun, G., Kim, H., Tai Kim, J., Effects of occupancy and lighting use patterns on lighting energy consumption, Energy and Buildings, 46 (2012), pp. 152-158
  48. Bodart, M., De Herde, A., Global energy savings in offices buildings by the use of daylighting, Energy and Buildings, 34 (2002), pp. 421-429

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence