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Empirical Study of How Traffic Intensity Detector Parameters Influence Dynamic Street Lighting Energy Consumption: A Case Study in Krakow, Poland

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  • Igor Wojnicki

    (Department of Applied Computer Science, AGH University of Science and Technology, Al.Mickiewicza 30, 30-059 Kraków, Poland)

  • Leszek Kotulski

    (Department of Applied Computer Science, AGH University of Science and Technology, Al.Mickiewicza 30, 30-059 Kraków, Poland)

Abstract

The deployment of dynamic street lighting, which adjusts lighting levels to fulfill particular needs, leads to energy savings. These savings contribute to the overall lighting infrastructure maintenance cost. Yet another contribution is the cost of traffic intensity data. The data is read directly from sensor systems or intelligent transportation systems (ITSs). The more frequent the readings are, the more costly they become, because of hardware capabilities, data transfer and software license costs, among others. The paper investigates a relationship between the frequency of readings, in particular the averaging window size and step, and achieved energy savings. It is based on a simulation, taking into account a representative part of a city and traffic intensity data, which span over a period of one year. While the energy consumption reduction is simulated, all data, including each luminaire power setting, induction loop locations and street characteristics, come from a representative sample of the city of Krakow, Poland. Controlling the power settings complies with the lighting standard CEN/TR 13201. Analysis of the outcomes indicates that the shorter the window size or step are, the more energy saving that is available. In particular, for the previous standard CEN/TR 13201 2004, having the window size and step at 15 min results in 26.75% of energy saving, while reducing these values to 6 min provides 27%. Savings are more profound for the current standard (CEN/TR 13201 2014), assuming a 15 min size and step results in 47.43%, while having a 6 min size and step provides 47.69%. The results can serve as a guideline for identifying the economic viability of dynamic lighting control systems. Additionally, it can be observed that the current lighting standard provides far greater potential for dynamic control then the previous standard.

Suggested Citation

  • Igor Wojnicki & Leszek Kotulski, 2018. "Empirical Study of How Traffic Intensity Detector Parameters Influence Dynamic Street Lighting Energy Consumption: A Case Study in Krakow, Poland," Sustainability, MDPI, vol. 10(4), pages 1-16, April.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:1221-:d:141514
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    References listed on IDEAS

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    1. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    2. Igor Wojnicki & Sebastian Ernst & Leszek Kotulski, 2016. "Economic Impact of Intelligent Dynamic Control in Urban Outdoor Lighting," Energies, MDPI, vol. 9(5), pages 1-14, April.
    3. repec:ipt:iptwpa:jrc47967 is not listed on IDEAS
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    Citations

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    Cited by:

    1. Cheng-Hsien Chen & Shau-Wei Hsu & Tsung-Hsun Yang & Ching-Cherng Sun, 2023. "Design of an Equipped Vehicle for In Situ Road Lighting Measurement," Sustainability, MDPI, vol. 15(13), pages 1-15, July.
    2. Xiaodong Xu & Xinhan Xu & Peng Guan & Yu Ren & Wei Wang & Ning Xu, 2018. "The Cause and Evolution of Urban Street Vitality under the Time Dimension: Nine Cases of Streets in Nanjing City, China," Sustainability, MDPI, vol. 10(8), pages 1-19, August.
    3. Chaiyan Jettanasen & Atthapol Ngaopitakkul, 2019. "Characteristics and Effects of Conducted Emission from Grid-Connected and Stand-Alone Micro-Inverters in a Nano-Grid Road Lighting System," Sustainability, MDPI, vol. 11(20), pages 1-14, October.
    4. Sebastian Ernst & Marek Łabuz & Kamila Środa & Leszek Kotulski, 2018. "Graph-Based Spatial Data Processing and Analysis for More Efficient Road Lighting Design," Sustainability, MDPI, vol. 10(11), pages 1-18, October.
    5. Alina Svechkina & Tamar Trop & Boris A. Portnov, 2020. "How Much Lighting is Required to Feel Safe When Walking Through the Streets at Night?," Sustainability, MDPI, vol. 12(8), pages 1-19, April.
    6. Laura Moretti & Giuseppe Cantisani & Luigi Carrarini & Francesco Bezzi & Valentina Cherubini & Sebastiano Nicotra, 2019. "Italian Road Tunnels: Economic and Environmental Effects of an On-Going Project to Reduce Lighting Consumption," Sustainability, MDPI, vol. 11(17), pages 1-13, August.
    7. László Balázs & Ferenc Braun & József Lengyel, 2023. "Energy Saving Potential of Traffic-Regulated Street Lighting," Sustainability, MDPI, vol. 15(8), pages 1-15, April.
    8. Adam Sȩdziwy & Artur Basiura & Igor Wojnicki, 2018. "Roadway Lighting Retrofit: Environmental and Economic Impact of Greenhouse Gases Footprint Reduction," Sustainability, MDPI, vol. 10(11), pages 1-11, October.
    9. Fouad Agramelal & Mohamed Sadik & Youssef Moubarak & Saad Abouzahir, 2023. "Smart Street Light Control: A Review on Methods, Innovations, and Extended Applications," Energies, MDPI, vol. 16(21), pages 1-42, November.
    10. Igor Wojnicki & Konrad Komnata & Leszek Kotulski, 2019. "Comparative Study of Road Lighting Efficiency in the Context of CEN/TR 13201 2004 and 2014 Lighting Standards and Dynamic Control," Energies, MDPI, vol. 12(8), pages 1-14, April.
    11. Lambros T. Doulos & Ioannis Sioutis & Aris Tsangrassoulis & Laurent Canale & Kostantinos Faidas, 2020. "Revision of Threshold Luminance Levels in Tunnels Aiming to Minimize Energy Consumption at No Cost: Methodology and Case Studies," Energies, MDPI, vol. 13(7), pages 1-23, April.

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