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A simple and accurate model for the design of public lighting with energy efficiency functions based on regression analysis

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  • Rabaza, Ovidio
  • Gómez-Lorente, Daniel
  • Pérez-Ocón, Francisco
  • Peña-García, Antonio

Abstract

In this study, new relationships between the energy efficiency of street lighting systems, street width, and luminaire height were derived from the analysis of a large sample of outputs, generated with a software application widely used for lighting design. The result was a quadratic polynomial that perfectly fit the relationships obtained and whose coefficients characterize each type of luminaire. This greatly simplifies the design of lighting facilities because it only uses one equation, but at the same time, takes all necessary variables into account. The procedure maximized the energy efficiency of the street lighting systems, as far as conditions allowed, and greatly facilitated the calculation of the parameters of a basic lighting installation, according to CIE (International Commission on Illumination) recommendations.

Suggested Citation

  • Rabaza, Ovidio & Gómez-Lorente, Daniel & Pérez-Ocón, Francisco & Peña-García, Antonio, 2016. "A simple and accurate model for the design of public lighting with energy efficiency functions based on regression analysis," Energy, Elsevier, vol. 107(C), pages 831-842.
    • Handle: RePEc:eee:energy:v:107:y:2016:i:c:p:831-842
    DOI: 10.1016/j.energy.2016.04.078
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    References listed on IDEAS

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    1. Kostic, Miomir & Djokic, Lidija, 2009. "Recommendations for energy efficient and visually acceptable street lighting," Energy, Elsevier, vol. 34(10), pages 1565-1572.
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    1. Ovidio Rabaza & Evaristo Molero-Mesa & Fernando Aznar-Dols & Daniel Gómez-Lorente, 2018. "Experimental Study of the Levels of Street Lighting Using Aerial Imagery and Energy Efficiency Calculation," Sustainability, MDPI, vol. 10(12), pages 1-16, November.
    2. Antonio Peña-García & Ferdinando Salata, 2020. "The Perspective of Total Lighting as a Key Factor to Increase the Sustainability of Strategic Activities," Sustainability, MDPI, vol. 12(7), pages 1-8, April.
    3. Michelangelo Scorpio & Roberta Laffi & Massimiliano Masullo & Giovanni Ciampi & Antonio Rosato & Luigi Maffei & Sergio Sibilio, 2020. "Virtual Reality for Smart Urban Lighting Design: Review, Applications and Opportunities," Energies, MDPI, vol. 13(15), pages 1-26, July.
    4. Han, Yongming & Wu, Hao & Geng, Zhiqiang & Zhu, Qunxiong & Gu, Xiangbai & Yu, Bin, 2020. "Review: Energy efficiency evaluation of complex petrochemical industries," Energy, Elsevier, vol. 203(C).
    5. Enrique Navarrete-de Galvez & Alfonso Gago-Calderon & Luz Garcia-Ceballos & Miguel Angel Contreras-Lopez & Jose Ramon Andres-Diaz, 2021. "Adjustment of Lighting Parameters from Photopic to Mesopic Values in Outdoor Lighting Installations Strategy and Associated Evaluation of Variation in Energy Needs," Sustainability, MDPI, vol. 13(8), pages 1-14, April.
    6. Salvia, Amanda Lange & Brandli, Luciana Londero & Leal Filho, Walter & Locatelli Kalil, Rosa Maria, 2019. "An analysis of the applications of Analytic Hierarchy Process (AHP) for selection of energy efficiency practices in public lighting in a sample of Brazilian cities," Energy Policy, Elsevier, vol. 132(C), pages 854-864.

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