Street Lighting Simulation for Energy Efficiency Improvement

The world population has grown exponentially in the last few decades. In the most of the world’s big cities, it is very difficult to provide the resources like energy, water, transportation and other essential services to the public due to the increase in the demands on resources and infrastructure. Internet of Things (IoT) is a technology that makes possible to keep the cities green and safe by interconnecting the devices, vehicles and infrastructure so that the energy and water consumption can be reduced and quality of the people can be improved. The objective of the smart cities could be to increase the economic growth, to construct a clean and sustainable environment, to enhance the income of the people and to make the transparent governance of the city. This chapter provides the need for Smart Street Lighting in smart cities and the suggestions for the implementation. Smart Street Lighting Framework which reduces the cost and the energy consumption is proposed. The present implementations of Intelligent street lighting around the world are also discussed.

Street Lighting is an important factor for ensuring safety in the city and instilling a sense of security in the mind of the citizens. But the cost associated with it is quite high which is borne by the local municipalities. Recent development in the lighting devices has seen a paradigm shift in the types of devices used which has led to little savings in energy consumption, but a lot remains wasted. Smart street lighting is a cost-effective solution in an urban environment which compromises of advance wireless communication techniques, low cost LED lights and additional sensors which controls the intensity of light. This new system has significant cost and energy savings over the conventional switching ON-OFF method. This paper presents a case study of smart lighting system in Nagpur smart city where one of the goals was to reduce the carbon footprint by reducing the energy consumption. This was achieved by replacing the outdated 320 street luminaries and integrating additional 63 LED lights with motion detection smart lighting system. The deployed intelligent street lighting system of Nagpur smart city has drastically reduced the energy consumption by approximately 55 % per month, while maintaining the lighting norms for the pedestrians and vehicles.

Intelligent street lighting refers to public street lighting that adapts to movement by pedestrians, cyclists and cars. This type of lighting is different from traditional, stationary illumination, or dimmable street lighting that dims at predetermined times. Intelligent street lighting, also referred to as adaptive street lighting, dims when no activity is detected, but brightens when movement is detected. Apart from that in this model of intelligent street lighting the lights will be configured to interact with each other to inform further lights to turn on or off when activity is detected near them. This ensures that people always walk in well-lit areas but area where activity is not detected remains dark thus saving energy. The lights will also be fitted with sensors to detect available sunlight initially and only come into action when required instead of predetermined times, it will also have access to a web API that provides average sunrise and sunset times in the region to save energy by reducing usage of the sensor itself.

The paper discusses a modern concept of smart street lighting that for illuminating city streets implies the use of special street lamps controlled via intelligent platforms. These platforms can regulate the intensity of lighting according to environmental conditions. At daybreak or when there is no people around, lamps’ brightness automatically decreases (or the lights entirely go down), which helps save electrical energy. As the result, expenditures from public funds on street lighting are reduced and the impact of electric power stations on the environment decreases. Street lighting is an essential part of the city infrastructure, since it performs several functions at ones. Firstly, it provides a sufficient level of illumination for traffic networks and pedestrian areas at night time, which not only enables reducing the number of traffic collisions and injuries, but also makes life of car drivers more convenient. Moreover, properly designed street lighting including street lamps on avenues, boulevards and in yards reduces the level of urban crime. Street lightning in Russia annually consumes approximately 7 billion kW/h of electric power, which is equivalent to 16 billion rubles. While producing such an amount of electric energy, millions of tons of various exhausts pollute the atmosphere. Smart street lighting systems help reduce the demand in electrical energy for outdoor illumination. The most important indicator of a civilized city is a well-lit roadway for transport – motorways. For transport on roads, various street lighting fixtures are used, but the most popular are energy-saving gas-discharge lamps, which effectively achieve full compliance with the standards and requirements for road lighting.

Street and public area lighting is a key service provided by municipal government. The public lighting sector is playing an important role in providing convenience, enhancing safety and security, promoting economic development, creation of friendly environment, as well as increasing the aesthetic appeal of surrounding property. The energy consumption in the street lighting sector, whether in public lighting or private users, constitutes a high percentage of the total energy used. Lighting conditions in streets of city of Tirana are currently at a level, which in many cases does not satisfy the requirements set out by legislation and standards. The study is undertaken with the request of Ministry of Infrastructure and Energy with goal to identify the possibility of applying new street lighting systems in Tirana, in order to draft concrete strategies for the future of street lighting in Albania. The study was focus on the opportunities and recommendations for the development and installation of LED technologies in the street lighting of Tirana. The study presented in this paper is completely based on the detailed analysis of the current state of the street lighting system in the Municipality of Tirana by visits and measurements, full information taken by municipality, interviews with responsible people of street lights system, different simulations based on DIALux software for new technology proposed. The study has estimated a great potential electrical energy savings by replacing existing street lighting lamps retrofits with LED in municipality of Tirana, around 33%, which is 4.6 million kWh/year, effecting a reduction of 1.85 million kg CO2 emission. The findings presented in the paper provide information on energy savings opportunities, which can be readily adopted by Municipalities of Albania, in their pursuit of energy and financial savings in street lighting sector.

At this stage, the level of urbanization in China is constantly improving, and the construction of “smart city” is gradually included in the ranks of national urban planning. As an important part of smart cities, intelligent street light are welcoming unprecedented development opportunities. The traditional street light control system generally adopts the methods of centralized line control,human inspection, and computer-side web monitoring. Aim at the lag of traditional street lamp management, and lack of real-time monitoring and remote control, this thesis designs a set of intelligent street light monitoring system based on NB-IoT (Narrow Band-Internet of Things).The system realizes the real-time control of street lighting system, environmental monitoring, spray cooling and dust suppression, etc. Cloud technology is used to calibrate the geographic location information and working status information of each street lamp. The test results show that the system is stable in operation and reliable in data transmission, reducing the cost and energy consumption of the traditional street lamp control nodes, and realizing the remote monitoring and intelligent management of the status of urban street lamps by the terminal equipment.

Street lighting is an important part of the energy consumption of cities. With suitable smart lighting systems that increase energy efficiency, it is possible to save on lighting costs substantially. Intelligent street lighting systems generally consist of lamps, ballast and dimming devices located in the area to be illuminated, control units placed in different lighting zones, and central management systems that can manage and monitor these regional controls. With smart lighting systems suitable for energy efficiency, it is possible to save a great deal of lighting costs while protecting the environment. When current projects are examined, it is seen that up to 80% energy savings can be achieved when automation systems are used in street lighting. There is a need for an approach that controls the luminous flux without reducing the driver's safety and comfort, and that performs dimming studies using machine learning methods. In this paper, the smart street lighting system developed jointly by ISBAK and Panasonic is explained.

Conventional street lighting systems in most of the areas are Online at regular intervals of time irrespective of the seasonal variations. The street lights are simply switched on at afternoon and turned off in the morning. The consequence is that a large amount of Power is wasted meaninglessly. As energy consumption is an issue of increasing interest, possible energy savings in public street lighting systems are recently discussed from different viewpoints. The purpose of this work is to describe the Smart Street Lighting system, an approach to accomplish the demand for flexible public lighting systems using a Programmable Logic controller (PLC). The main difference from other computers is that PLCs are armoured for severe conditions such as dust, moisture, heat, cold etc., and have the facility for extensive input/output (I/O) arrangements. In the proposed paper, street lights are controlled using millennium 3 PLC taking the seasonal variations into consideration.

The use of LED lights in smart street lighting to save energy is efficient and very common in many developed cities. However, such a system results in higher initial costs, which may discourage smaller towns and villages from its purchasing. This paper therefore deals with the design and development of a smart street lighting control system for smaller cities and villages. Such a system is required to be economical from the perspective of development and production. Considering other requirements such as platform independence, high availability and broad support, we proposed to build a system as a web application using a custom light control service component. The result is a web application that consists of a user interface served by a web server and an application server used to communicate with light control service. In addition, the system is designed as a geographical information system to be easy to use for managing street lights in groups or individually, while displaying them on the map. The system allows automatic sensor-based light intensity modulation by default with the possibility of manual adjustment or override of the illumination. It also includes a device error notification system with a tool to navigate faulty devices. The presented system is a low-cost solution for intelligent street lighting control designed for smaller cities or villages. They can apply the designed architecture of the system and the specific technologies suitable because of their low-cost implementation.

The rapid development of urban areas has considerably increased energy spending, particularly in street lighting system. Traditional streetlight managing method often lack optimization, leading to inefficiencies and higher operational costs. This research proposes an Intelligent Streetlight Control System (ISCS) to enhance energy efficiency by with passion adjusting lighting based on real-time data. The system combines multiple data sources, including time, location, ambient light levels, traffic count, and energy consumption, to optimize explanation. Data pre-processing engross Min-Max scaling for normalization and Fast Fourier Transform (FFT) for feature extraction. The Energy Valley Optimizer (EVO) fine-tunes the Dynamic Elman Neural Network (DENN) to predict traffic flow and adjust street lighting accordingly. The system is executed using Python, and experimental results display that ISCS effectively decreases energy consumption by optimizing streetlight presentation in response to environmental conditions.The EVO-DENN model outperforms conventional control methods in both energy efficiency and prediction accuracy, proving its likelihood for large-scale urban deployment. Key performance metrics include an operational duration of 12 hours, a power rating of 140W, power consumption of 0.698W, daily unit consumption of 0.695W, and an energy savings rate of 43.25%. The findings indicate that integrating intelligent streetlight control enhances sustainability in urban infrastructure, providing a foundation for smarter, adaptive cities. By implementing AI-driven energy management, the proposed system contributes to cost reduction and environmental conservation, making it a significant step toward the development of intelligent urban ecosystems. Future research could focus on incorporating renewable energy sources and expanding the system’s adaptability to different urban environments worldwide.

Street lighting consumes a substantial amount of energy and improving its efficiency is a significant challenge. A promising approach to enhance the efficiency is through the use of intelligent control systems. Intelligent street lighting utilizing LED-based luminaries are made to be energy efficient through using adaptable/dynamic illumination and around the clock lamp monitoring. In this work, an intelligent LED street lighting solution is proposed based on ZigBee wireless network and using the ZigBee Cluster Library (ZCL) messaging protocol to accelerate the development of the control application meanwhile allowing for Over The Air programming (OTA) of the wireless nodes after deployment. An experimental prototype for the proposed solution was implemented using the ZigBee Cluster Libraries, a sample control application was developed and ZCL functions were tested with the prototype.

A Smart Street light (SSL) is a public lighting that incorporates technology to introduce a real time monitoring functionalities. SSL is known to be a cost-effective and sustainable choice for cities and utilities today. In enabling cities to provide proper amount of street light for local conditions, installing SSL will improve citizen satisfaction regarding security and safety, while bringing municipalities significant savings in power consumption and lighting system maintenance. Tenaga Nasional Berhad (TNB) through its research arm, TNB Research (TNBR) has recently carried out a pilot study on the feasibility of SSL system by using energy efficient light-emitting diode (LED) lighting technology. In the study, two (2) SSL technologies have been selected and evaluated through field trial which are Securemesh 2.4 GHz Neighborhood Area Network (NAN) and Ultra Narrowband (UNB). Both SSL systems have been pilot tested at selected areas in Melaka state. This paper shall discuss their technical performance such as functionality, reliability and compatibility that have been evaluated in the study.

Good street lighting planning is essential, especially in areas prone to accidents and crime. Good street lighting can reduce the risk of accidents and increase the sense of security in public areas, providing security, convenience, and comfort for road users, especially at night or in bad weather conditions. However, street lighting is often a significant source of energy consumption. Therefore, optimising the street lighting system to improve energy efficiency is necessary. The study results showed that the existing lighting system using 250 W high-pressure sodium (HPS) lamps has weaknesses in terms of energy efficiency and light distribution quality. Simulations using Dialux showed that the average luminance of existing lighting only reached 0.6 cd/m² with a uniformity level of 0.4, and energy consumption reached 20,000 W along the road. Lighting optimization using 120 W LED lamps provides significant improvements in energy efficiency and lighting quality. The average luminance increased to 0.8 cd/m² with a uniformity of 0.6, while energy consumption decreased by 52%, from 20,000 W to 9,600 W. In addition, the glare level decreased from 30 to 25, indicating an increase in visual comfort. These results indicate that the implementation of LED lights can not only improve the quality of street lighting but also have a positive impact on energy efficiency and reduced operating costs.

The main purpose of smart city is to improve the quality of life, improve the efficiency of life, and save the energy resources of life, which is in line with the current global concept of low-carbon environmental protection, energy saving and emission reduction, and ecological sustainable development. Under the process of smart city, the development of urban public space is also committed to meeting the material and spiritual needs of residents’ lives. For the system hardware design, the street lamp node, and the concentrator node hardware design, the sensing node is composed of multiple sensors. Its main components are temperature sensor, infrared sensor, sound sensor, and light intensity sensor, which, respectively, realize the collection of temperature, infrared, sound, and light intensity information. The street light sensing system uses multisensor information fusion technology to detect the situation of people and vehicles in real time, so that people and vehicles can turn on the street lights and turn off the street lights of unmanned vehicles. Adjust the street light switch according to the intelligent analysis of the lighting demand scene in order to enhance the accuracy of the system to identify the lighting demand scene. This enables the system to provide safe lighting conditions for urban traffic while saving the power consumption of urban lighting. The sensor system of the street light randomly selects the detection results of temperature and humidity within a certain period of time. The error rate of the final test result is 1/2 of that of the traditional test, and the accuracy is far lower than that of the traditional measurement method. Regarding the lighting system of street lamps and public art in urban public spaces, it is worthy of extensive promotion to control street lamp lighting through sensor information fusion technology and reduce energy consumption.

The amount of greenhouse gas emissions from streetlights is equivalent to 2.6 million cars with as many as 26 million streetlights in the United States. The proposed IoT controller integrates sensors to make these streetlights as hubs for smart environment monitoring with effective energy usage. Conservation of energy is one of the main concerns in the modern era, and energy coming from the sun can be utilized efficiently alongside a smart streetlight management system instead of conventional streetlight management techniques. Additionally, with streetlights being present throughout a city, the opportunity to collect city-wide weather data is proposed. To this end, a solar-powered IoT-based smart street lighting and environmental monitoring system is proposed. The proposed energy-efficient IoT-based system uses a microcontroller to control light-emitting diode (LED) streetlights depending on lighting conditions and vehicle detection, ensuring that the streetlights can be turned on when needed.