MATHEMATICAL MODELING OF COLOR INFLUENCE IN DIALUX SOFTWARE IN INTERIOR LIGHTING BUILDING

Authors

  • Merimé SOUFFO TAGUEU Department of Physics, Faculty of Science, University of Yaoundé I, P.O. Box 812, Yaoundé, Cameroon. Author
  • Loic Steve YAKAM NDJOTCHO Department of Mechanical and Industrial Engineering, National Advanced School of Engineering of Yaoundé, University of Yaoundé I, P.O. Box 8390, Yaoundé, Cameroon. Author
  • Benoît NDZANA Department of Electrical and Telecommunications Engineering, National Advanced School of Engineering of Yaoundé I, University of Yaoundé I, P.O. Box 8390, Yaoundé, Cameroon. Author

Keywords:

Lighting, Mathematical Model, DIALux, Colors, Energy Savings

Abstract

The energy consumed by the lighting of the buildings represents a not negligible part of the total energy. LED lighting has significantly reduced this part with advantages over the reduction of greenhouse gas emissions. Much more related to the standard related to lighting, many studies using optimization algorithms have reduced the amount of lux emitted by lamps to stay close to normative values. In this article, we propose a mathematical model for estimating the coefficient of influence of colors on the lighting level of buildings. The model shows that the value of the level of lighting is strongly influenced when using primary colors and that this influence decreases for the other colors (secondary, tertiary, etc.). The interest of such a model lies in the possibility for the user to have an idea of the change in the level of illumination of a room when it changes color. Furthermore, the need for energy savings can be predicted without the need for prior simulation on software such as DIALux to know the values of the lighting levels to be reached. This saves computing time.

 

References

Consumption of energy, 2017. https://ec.europa.eu/eurostat/statisticsexplained/ index.php?title=Archive: Consumption of energy.

J. Popoviü-Gerber, J. Oliver, N. Cordero, T. Harder, J. Cobos, M. Hayes, S. O'Mathuna and E. Prem, "Power Electronics Enabling Efficient Energy Usage: Energy Savings Potential and Technological Challenges", IEEE Transactions on Power Electronics, vol. 27, no. 5, pp. 2338-2353, 2012

DUBOIS, Marie-Claude et BLOMSTERBERG, Åke. Energy saving potential and strategies for electric lighting in future North European, low energy office buildings: A literature review. Energy and buildings, 2011, vol. 43, no 10, p. 2572-2582.

LEE, Jae-Wook, JUNG, Hyung-Jo, PARK, Ji-Young, et al.Optimization of building window system in Asian regions by analyzing solar heat gain and daylighting elements. Renewable energy, 2013, vol. 50, p. 522-531.

Baldinelli, G.; Asdrubali, F.; Baldassarri, C.; Bianchi, F.; D’Alessandro, F.; Schiavoni, S.; Basilicata, C. Energy and environmental performance optimization of a wooden window: A holistic approach. Energy Build. 2014, 79, 114–131.

BICHIOU, Youssef et KRARTI, Moncef. Optimization of envelope and HVAC systems selection for residential buildings. Energy and Buildings, 2011, vol. 43, no 12, p. 3373-3382.

RAPONE, Gianluca et SARO, Onorio. Optimisation of curtain wall facades for office buildings by means of PSO algorithm. Energy and Buildings, 2012, vol. 45, p. 189-196.

OUARGHI, Ramzi et KRARTI, Moncef. Building Shape Optimization Using Neural Network and Genetic Algorithm Approach. Ashrae transactions, 2006, vol. 112, no 1.

TUHUS-DUBROW, Daniel et KRARTI, Moncef. Genetic-algorithm based approach to optimize building envelope design for residential buildings. Building and environment, 2010, vol. 45, no 7, p. 1574-1581.

PRIANTO, Eddy et DEPECKER, Patrick. Optimization of architectural design elements in tropical humid region with thermal comfort

approach. Energy and buildings, 2003, vol. 35, no 3, p. 273-280.

Asdrubali, F.; D’Alessandro, F.; Schiavoni, S. A review of unconventional sustainable building insulation materials. Sustain. Mater. Technol. 2015, 4, 1–17.

WANG, Jiangjiang, ZHAI, Zhiqiang John, JING, Youyin, et al.Particle swarm optimization for redundant building cooling heating and power system. Applied Energy, 2010, vol. 87, no 12, p. 3668-3679.

Ebrahim Solgi , Zahra Hamedani , Ruwan Fernando , Henry Skates , Nnamdi Ezekiel Orji , A Literature Review of Night Ventilation Strategies in Buildings, Energy & Buildings (2018), DOI: 10.1016/j.enbuild.2018.05.052

J. Pfafferott, S. Herkel, and M. Wambsganß, "Design, monitoring and evaluation of a low energy office building with passive cooling by night ventilation," Energy and Buildings, vol. 36, pp. 455-465, 2004.

J. Landsman, "Performance, Prediction and Optimization of Night Ventilation across Different Climates," 2016

DJURIC, Natasa, NOVAKOVIC, Vojislav, HOLST, Johnny, et al. Optimization of energy consumption in buildings with hydronic heating systems considering thermal comfort by use of computer-based tools. Energy and Buildings, 2007, vol. 39, no 4, p. 471-477.

A. M. Khudhair and M. M. Farid, "A review on energy conservation in building applications with thermal storage by latent heat using phase change materials," Energy conversion and management, vol. 45, pp. 263-275, 2004.

Juan F. De Paz, Javier Bajo, Sara Rodr´ıguez, Gabriel Villarrubia, Juan M. Corchado, Intelligent system for lighting control in smart cities, Information Sciences (2016), doi: 10.1016/j.ins.2016.08.045

Kandasamy, Nandha Kumar, Karunagaran, Giridharan, SPANOS, Costas, et al. Smart lighting system using ANN-IMC for personalized lighting control and daylight harvesting. Building and Environment, 2018, vol. 139, p. 170-180.

W. Si, H. Ogai, K. Hirai, H. Takahashi, An Improved PSO Method for Energy Saving System of Office Lighting, Proceedings of SICE Annual Conference (2011) 1533–1536.

M. Corcione, L. Fontana, Optimal design of outdoor lighting systems by genetic algorithms, Light. Res. Technol. 35 (2003) 261–277.

M. Krarti, P. M. Erickson, T. C. Hillman, A simplified method to estimate energy savings of artificial lighting use from daylighting, Building and Environment 40 (6) (2005) 747-754.

P. Ihm, A. Nemri, M. Krarti, Estimation of lighting energy savings from daylighting, Building and Environment 44 (3) (2009) 509-514.

S.Y. Chen, J.W. Zhang, Intelligent Lighting Control for Vision-Based Robotic Manipulation”, IEEE Transactions on Industrial Electronics 59 (2012) 3254–3263

J. Liu, W. Zhang, X. Chu, Y. Liu, Fuzzy logic controller for energy savings in a smart led lighting system considering lighting comfort and daylight, Energy and Buildings 127 (2016) 95-104.

Z. Wang, Y. K. Tan, Illumination control of led systems based on neural network model and energy optimization algorithm, Energy and Buildings 62 (2013) 514-521.

Y.J. Wen, A.M. Agogino, Personalized dynamic design of networked lighting for energy-efficiency in open-plan offices, Energy Build. 43 (2011) 1919–1924

D. Tran, Y. K. Tan, Sensorless illumination control of a networked led-lighting system using feedforward neural network, IEEE Transactions on Industrial Electronics 61 (4) (2013) 2113-2121.

A.D. Galasiu, M.R. Atif, Applicability of daylighting computer modeling in real case studies: comparison between measured and simulated daylight availability and lighting consumption, Building and Environment 37 (2002) 363–377.

Woolf, L. D. (1999). Confusing color concepts clarified. The Physics Teacher, 37(4), 204–206.doi:10.1119/1.880230

Light and lighting-lighting of work places ? part 1 : Indoor work places, June 2011. European Committee for Standardization.

MADIAS, Evangelos-Nikolaos D., KONTAXIS, Panagiotis A., et TOPALIS, Frangiskos V. Application of multi-objective genetic algorithms to interior lighting optimization. Energy and Buildings, 2016, vol. 125, p. 66-74.

[33] Yao-Jung Wen and AM Agogino. Control of wireless-networked lighting in open-plan offices. Lighting Research & Technology, 43(2) :235–248, 2011.

Michael Fischer, Kui Wu, and Pan Agathoklis. Intelligent illumination model-based lighting control. In 2012 32nd International Conference on Distributed Computing Systems Workshops, pages 245–249. IEEE, 2012.

Merimé Souffo Tagueu, Benoît Ndzana, Color Influence and Genetic Algorithm Optimization in Interior Lighting Building, American Journal of Electrical Power and Energy Systems. Vol. 8, No. 6, 2019, pp. 165-175.

E. Brembilla, C.J. Hopfe & J. Mardaljevic (2018) Influence of input reflectance values on climate-based daylight metrics using sensitivity analysis, Journal of Building Performance Simulation, 11:3, 333-349

Perez, R., R. Seals, and J. Michalsky. 1993. “All-Weather Model for Sky Luminance Distribution–Preliminary Configuration and Validation.” Solar Energy 50 (3): 235–245.

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Published

2024-04-20

How to Cite

MATHEMATICAL MODELING OF COLOR INFLUENCE IN DIALUX SOFTWARE IN INTERIOR LIGHTING BUILDING. (2024). INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING AND TECHNOLOGY (IJEET), 15(2), 12-22. https://iaeme-library.com/index.php/IJEET/article/view/IJEET_15_02_002