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

Abstract

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.