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Sustainability 2016, 8(1), 13; doi:10.3390/su8010013

Sustainable Street Lighting Design Supported by Hypergraph-Based Computational Model

Department of Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, Kraków 30-059, Poland
Academic Editor: Marc A. Rosen
Received: 20 October 2015 / Revised: 9 December 2015 / Accepted: 18 December 2015 / Published: 30 December 2015
(This article belongs to the Section Sustainable Engineering and Science)
View Full-Text   |   Download PDF [837 KB, uploaded 30 December 2015]   |  

Abstract

Street lighting systems are significant energy consumers in urban environments. The important step toward the reduction of this energy consumption and, thus, finding a balance between functional requirements and savings-related demands, was introducing LED-based light sources. There still exists, however, a margin for further savings, which is associated with well-tailored designs of road lighting installations. The critical impediment that has to be overcame beforehand is the computational complexity related to preparing such a well-suited design. To make this approach feasible, we propose using the formal graph-based model, enabling efficient heuristic computations. In this article, we demonstrate several real-life cases showing a coarse estimation of potential savings in terms of reduced CO2 emission. The presented results are expressed in kWh of saved energy, metric tones of CO2 , but also as a volume of combusted fuels, to make the assessment more tangible. View Full-Text
Keywords: street lighting; energy efficiency; photometric computations; CO2 reduction street lighting; energy efficiency; photometric computations; CO2 reduction
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Sȩdziwy, A. Sustainable Street Lighting Design Supported by Hypergraph-Based Computational Model. Sustainability 2016, 8, 13.

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