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Intelligent control for energy-positive street lighting

Author

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  • Kovács, András
  • Bátai, Roland
  • Csáji, Balázs Csanád
  • Dudás, Péter
  • Háy, Borbála
  • Pedone, Gianfranco
  • Révész, Tibor
  • Váncza, József

Abstract

The paper investigates the application of solar energy in public lighting for realizing a street lighting sub-grid with positive yearly energy balance. The focus is given to the central controller, which ensures the adaptive behavior of the overall system and provides smart city services to the end users via its web-based user interface. A functionality of the controller of special interest is the optimization of the energy management of the system, i.e., determining when to sell and buy electricity to/from the grid, in order to minimize the cost of electricity (or to maximize the profit) subject to a given, time-of-use variable energy tariff. This requires precise forecasts of the energy produced and consumed, as well as appropriate robust optimization techniques that guarantee that the system bridges potential power outages of moderate duration in island mode. The algorithms implemented in the controller are presented in detail, together with the evaluation of the operation of a deployed physical prototype with 191 luminaries over a horizon of six months, based on the monitoring data collected by the proposed controller.

Suggested Citation

  • Kovács, András & Bátai, Roland & Csáji, Balázs Csanád & Dudás, Péter & Háy, Borbála & Pedone, Gianfranco & Révész, Tibor & Váncza, József, 2016. "Intelligent control for energy-positive street lighting," Energy, Elsevier, vol. 114(C), pages 40-51.
    • Handle: RePEc:eee:energy:v:114:y:2016:i:c:p:40-51
    DOI: 10.1016/j.energy.2016.07.156
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    Cited by:

    1. Igor Wojnicki & Leszek Kotulski, 2018. "Improving Control Efficiency of Dynamic Street Lighting by Utilizing the Dual Graph Grammar Concept," Energies, MDPI, vol. 11(2), pages 1-15, February.
    2. László Balázs & Ferenc Braun & József Lengyel, 2023. "Energy Saving Potential of Traffic-Regulated Street Lighting," Sustainability, MDPI, vol. 15(8), pages 1-15, April.
    3. Tukymbekov, Didar & Saymbetov, Ahmet & Nurgaliyev, Madiyar & Kuttybay, Nurzhigit & Dosymbetova, Gulbakhar & Svanbayev, Yeldos, 2021. "Intelligent autonomous street lighting system based on weather forecast using LSTM," Energy, Elsevier, vol. 231(C).
    4. Mohammad K. Najjar & Eduardo Linhares Qualharini & Ahmed W. A. Hammad & Dieter Boer & Assed Haddad, 2019. "Framework for a Systematic Parametric Analysis to Maximize Energy Output of PV Modules Using an Experimental Design," Sustainability, MDPI, vol. 11(10), pages 1-24, May.
    5. Benedek, József & Sebestyén, Tihamér-Tibor & Bartók, Blanka, 2018. "Evaluation of renewable energy sources in peripheral areas and renewable energy-based rural development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 516-535.
    6. Antonio Ocana-Miguel & Jose Ramon Andres-Diaz & Manuel Jesús Hermoso-Orzáez & Alfonso Gago-Calderón, 2018. "Analysis of the Viability of Street Light Programming Using Commutation Cycles in the Power Line," Sustainability, MDPI, vol. 10(11), pages 1-14, November.
    7. 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.

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