Alberto Van Zeller
Research Subjects
Alberto Van Zeller has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Anibal T. de Almeida
Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal
1 shared publication - Fernando Martins
Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal
1 shared publication - Pedro Luis. Moura
Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal
1 shared publication - Sara Fradique
National Entity for the Energy Sector, Campus do Lumiar Edifício D, 1° Andar, 1649-038 Lisboa, Portugal
1 shared publication
Latest Publications
- Open Access
- 2 July 2026
- Published by MDPI AG in Electricity
- Vol. 7 (3) , 66
A Road-Segment-Level Energy Classification Framework for Public Lighting: From Algorithmic Assessment to Voluntary Energy Labels for Municipal Action
Public lighting can account for nearly 40% of municipal energy consumption in some European cities and plays a vital role in road safety, mobility, and the quality of public spaces. Despite notable efficiency gains from the widespread adoption of light-emitting diode (LED) technologies, the technical outputs of standards-based and installation-level assessment methods are not usually simple and communicable energy-performance labels for municipal decision-making. This study addresses this issue by introducing an algorithm-based framework for classifying energy performance in public lighting at the road-segment level. This approach translates existing lighting standards and efficiency indicators into a straightforward and understandable energy label, adapting the energy labelling concept, commonly used for buildings and appliances, to public space infrastructure. This framework is implemented through a national digital platform for public lighting classification, which has already attracted formal interest from more than 100 municipalities, indicating strong institutional uptake. The results indicate that road-segment-level energy classification is feasible and scalable as a voluntary tool to enhance municipal accountability and support informed decision-making. This study concludes that algorithmic energy labels for public lighting can support sustainable urban governance transparency, comparability and decision-making capacity, with future research aimed at building capacity for large-scale implementation and incorporating environmental, human health, and ecological impact considerations into the classification system.
- 2 July 2026
- Published by MDPI AG in Electricity
- Vol. 7 (3) , 66
Open AccessA Road-Segment-Level Energy Classification Framework for Public Lighting: From Algorithmic Assessment to Voluntary Energy Labels for Municipal Action
Public lighting can account for nearly 40% of municipal energy consumption in some European cities and plays a vital role in road safety, mobility, and the quality of public spaces. Despite notable efficiency gains from the widespread adoption of light-emitting diode (LED) technologies, the technical outputs of standards-based and installation-level assessment methods are not usually simple and communicable energy-performance labels for municipal decision-making. This study addresses this issue by introducing an algorithm-based framework for classifying energy performance in public lighting at the road-segment level. This approach translates existing lighting standards and efficiency indicators into a straightforward and understandable energy label, adapting the energy labelling concept, commonly used for buildings and appliances, to public space infrastructure. This framework is implemented through a national digital platform for public lighting classification, which has already attracted formal interest from more than 100 municipalities, indicating strong institutional uptake. The results indicate that road-segment-level energy classification is feasible and scalable as a voluntary tool to enhance municipal accountability and support informed decision-making. This study concludes that algorithmic energy labels for public lighting can support sustainable urban governance transparency, comparability and decision-making capacity, with future research aimed at building capacity for large-scale implementation and incorporating environmental, human health, and ecological impact considerations into the classification system.