Energy Efficient Street Lighting System Research Articles

Efficacious tuning in energy efficient street lighting

An energy efficient street lighting system is proposed in this paper to obtain a balance between energy savings and utility in terms of illumination by the street lights. The finite coverage of every street light equipped with the sensor is divided into zones according to the distance of the nearest pedestrian or vehicle with respect to that street light. The illumination of the street light is adjusted accordingly with respect to zones. Every street is divided into sections depending on the average distance between street lights. The parameters namely the energy savings as well as the utility of the lights in a section are defined in terms of the values of length of a zone and the factor of brightness decrement per zone. The best value of this decrement factor is determined by tuning to obtain energy efficiency. Simulation results highlight that the proposed work outperforms the existing method. As an outcome, the proposed scheme obtains a superior % of energy savings over existing work without falling below minimum utility for a small inter-distance.

Energy Efficient Street Lighting System Based on Microcontroller

This paper aims to present an Intelligent Street Light System which is used to control the intensity of street lights based on motion detection of people and vehicles and to turn on the LED lights only when required. The system provides a cost-effective and an energy efficient solution for street lighting applications. The system operates in two modes, Bright state and Dim State. Passive Infrared (PIR) Sensors are used for motion detection. On detection of motion, the LED Bulbs are put into BRIGHT state, which otherwise remain in DIM state. The change in intensity levels from DIM to BRIGHT and vice-versa is achieved by a dimmer circuit. Detection of motion is also communicated to neighboring street lights, over WiFi, which also then change their state to BRIGHT state. The microcontroller used is ESP8266.

Artificial Neural Network based Smart and Energy Efficient Street Lighting System: A Case Study for Residential area in Hosur

Smart city is the term described to integrate all facilities to the people in a frequently accessible manner. Street lighting system is one of the part of the facility provided in smart cities. The unwanted utilisation of the street lighting affects the economic status of the country indirectly. Power consumption through street lighting is major problem, hence action plan is taken to promote the reduction policies of the power consumption. Reducing the unnecessary power consumption is not a simple task, but with soft computing approaches power consumption can be reduced. The objective of this article is to present an ANN based energy efficient smart street lighting systems. The proposed design were implemented and executed in a residential area, Hosur and the results are carried out at different scenarios and various seasons. The decision making module exploits the analysis factors obtained via lighting sensor, motion sensor, PIR sensor, etc. artificial neural network and fuzzy logic controller makes an efficient decision making process for demand based utilisation and to avoid the unnecessary utilisation of street lights. The five levels of scenarios are tested and implemented in a real time. Through this work, the smart and energy efficiency street lighting system reduced the unwanted utilisation by 34% and reduced the power consumption rate of 13.5%.

A multi-criteria decision making approach for public lighting system selection

There are numerous and different ways to design an energy efficient street lighting system, but not always the best technical solution is the optimal economic solution as well. In this paper, we used two distinct software tools in order to obtain the optimal technical and economic solution for selecting street lighting technology. The first software used was DIALux, which is frequently applied in this field, assisting designers in choosing the most appropriate electrical installations and evaluating the technical performance of the chosen solutions. This tool determined the street lighting system variants for which there are predetermined configurations, so that the lighting parameters obtained are in accordance with the normative requirements of the lighting classes in which the roadways are included. Different ways of locating the luminaires and other parameters were changed to reach the best version that meets the qualitative requirements of the lighting technology. The second software used was the one developed by the authors, based on ELECTRE III method, which evaluated the technical solutions returned by DIALux against several criteria, taking into account the designer’s preferences and constraints. The optimal technical and economic solution was obtained after ranking the variants by their performance at each criterion. The simulation experiment and the results returned suggested that the combination of the two software tools is comprehensive and effective and it can be used in this type of decisions at large scale.