Unconventional Luminaire Layout Design by Genetic Algorithms

Zuzana Panska, Marek Balsky (), Rudolf Bayer and Michal Brejcha
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Zuzana Panska: Department of Electrical Power Engineering, Faculty of Electrical Engineering, Czech Technical University, 166 27 Prague, Czech Republic
Marek Balsky: Department of Electrical Power Engineering, Faculty of Electrical Engineering, Czech Technical University, 166 27 Prague, Czech Republic
Rudolf Bayer: Department of Electrical Power Engineering, Faculty of Electrical Engineering, Czech Technical University, 166 27 Prague, Czech Republic
Michal Brejcha: Department of Electrotechnology, Faculty of Electrical Engineering, Czech Technical University, 166 27 Prague, Czech Republic

Sustainability, 2024, vol. 16, issue 17, 1-12

Abstract: The dominant part of energy performance of a building consists of the consumption of heating and lighting. Both the heating and lighting systems of buildings work at their designed efficiency for most of the buildings’ lifetimes. Interference with existing systems is costly considering replacements and construction adjustments. Therefore, considerable effort must be put into the design of these systems during the building design phase. The article is focused on luminaire layout design strategy, which affects the number of luminaires in a building and therefore their power consumption and the sustainability of the building. A genetic algorithm with radiosity implemented has been used to find suitable placements of luminaires of a single type in a model room to decrease the number of luminaires as much as possible. The use of a genetic algorithm can reduce the number of luminaires by using an irregular grid of luminaire placement, and therefore decrease the power demand and increase the sustainability of the lighting system. Three outcomes of an optimal luminaire layout design are presented in this paper, including the design strategy conclusions. The results of the calculation outcomes were verified by software DIALux that is commonly used for designing lighting systems.

Keywords: lighting design; genetic algorithm; luminaire layout design; luminous intensity curve (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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