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Energy Efficiency
Published in: Energy Efficiency 3/2013

01-08-2013 | Original Article

Smart street lighting management

Authors: S. Pizzuti, M. Annunziato, F. Moretti

Published in: Energy Efficiency | Issue 3/2013

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Abstract

In this work, we propose a new street lighting energy management system in order to reduce energy consumption. The key idea we want to accomplish is that of “energy on demand” meaning that energy, in this case light, is provided only when needed. In order to achieve this goal, it is critical to have a reliable demand model, which in the case of street lighting turns out to be a traffic flow rate forecasting model. In order to achieve this goal, several methods on the 1-h prediction have been compared and the one providing the best results is based on artificial neural networks. Moreover, several control strategies have been tested and the one which gave the best energy savings is the adaptive one we carried out. Experimentation has been carried out on real data and the study shows that with the proposed approach, it is possible to save up to 50 % of energy compared to no regulation systems.
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Metadata
Title
Smart street lighting management
Authors
S. Pizzuti
M. Annunziato
F. Moretti
Publication date
01-08-2013
Publisher
Springer Netherlands
Published in
Energy Efficiency / Issue 3/2013
Print ISSN: 1570-646X
Electronic ISSN: 1570-6478
DOI
https://doi.org/10.1007/s12053-013-9195-9

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