LAPSE:2018.0995
Published Article
LAPSE:2018.0995
Towards Highly Energy-Efficient Roadway Lighting
Adam Sȩdziwy, Leszek Kotulski
November 27, 2018
The reports presented by consulting firms show that annual energy costs generated by 340 million streetlights are expected to reach $23.9 to $42.5 billion by 2025. Those numbers reveal a motivation behind the research aiming at optimizing outdoor lighting energy efficiency. They show that even a small unit improvement can yield large benefits due to the effect of scale. The development of solid state lighting solutions enables highly effective modernization of street lighting installations. It allows obtaining power saving not only by replacing high pressure lamps with LEDs but also by improving a design quality and by introducing a dynamic street lighting control. Both methods, however, are not feasible for industry-standard software tools due to the significant complexity related to a configuration optimization, especially for large-scale projects. The goal of this article is presenting the workaround to the complexity issue, which is based on application of graph methods. They enable optimizing lighting installations in the scale of a city by providing a scalable computational environment. The presented case study shows that, thanks to applying the proposed method, one can design a lighting system which has the energy consumption reduced by up to 70%.
Keywords
computational intelligence, Energy Efficiency, large-scale photometric computations, lighting design, smart grid
Suggested Citation
Sȩdziwy A, Kotulski L. Towards Highly Energy-Efficient Roadway Lighting. (2018). LAPSE:2018.0995
Author Affiliations
Sȩdziwy A: Department of Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland [ORCID]
Kotulski L: Department of Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland
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Journal Name
Energies
Volume
9
Issue
4
Article Number
E263
Year
2016
Publication Date
2016-04-01
Published Version
ISSN
1996-1073
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PII: en9040263, Publication Type: Journal Article
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LAPSE:2018.0995
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doi:10.3390/en9040263
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Nov 27, 2018
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CC BY 4.0
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Nov 27, 2018
 
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Calvin Tsay
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