A new street lighting control algorithm based on forecasted traffic data for electricity consumption reduction

Buildings, urban mobility and public lighting systems are promising areas for cities to reduce energy consumption. In this work, a smart city located in a central region of Italy was investigated and a new street lighting control algorithm was developed. The method is applied to manage the public lighting system of a real case study, where efficient technologies, such as LED lamps and control systems, are already installed. Preliminary on-site measurements of traffic and lighting parameters were carried out in specific streets chosen for the case studies. The analysis was supported with lighting simulations. Based on the results, a Python-based algorithm was developed to apply switching and dimming schedules to decrease the electricity consumption of the streets. A cost/benefit study was carried out and a preliminary analysis of the environmental impact of the proposed strategy is also included. The developed algorithm could be further improved based on other boundary conditions, such as daylighting and weather data.

• Record URL:
  • https://doi.org/10.1177/14771535231194536
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/14771535
• Supplemental Notes:
  • © The Chartered Institution of Building Services Engineers 2023.
• Authors:
  • Belloni, E
  • 0000-0002-3556-6501
  • Buratti, C
  • Lunghi, L
  • Martirano, L
• Publication Date: 2024-8

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 481-501
• Serial:
  • Lighting Research and Technology
  • Volume: 56
  • Issue Number: 5
  • Publisher: Sage Publications Limited
  • ISSN: 1477-1535
  • Serial URL: http://lrt.sagepub.com/

Subject/Index Terms

• TRT Terms: Algorithms; Benefit cost analysis; Energy consumption; Lighting systems; Street lighting; Traffic data
• Geographic Terms: Italy
• Subject Areas: Design; Energy; Highways;

Filing Info

• Accession Number: 01895974
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 13 2023 8:40AM