The broad implementation of light emitting diode (LED) light sources in public lighting has become a revolution in recent years. Their low power consumption and good performance (extremely low onset time, long lifetime, high efficacy) make LEDs an optimal solution in most outdoor applications. In addition, the white light emitted by the vast majority of LEDs used in public lighting and their good color rendering improve well-being, comfort, and safety in cities, especially in commercial zones and urban centers. However, regulations on light pollution that have been developed in some countries in parallel to the introduction of LED lighting impose strong constraints to white light emission, which is present due to the higher Rayleigh scattering of short wavelengths. These regulations request filtering blue wavelengths in some protected areas and thus limit the projects to high- or low-pressure sodium sources or amber LEDs. In this work, the pros and cons of white and amber LED lighting in rural areas are analyzed and compared through simulations made on a typical rural lighting situation and considerations based on efficiency, visual performance, nonvisual effects, and light pollution. The most important conclusion is that Rayleigh scattering seems to prevail in the current considerations on light pollution, whereas other important aspects affecting safety and sustainability are are not considered. Accurate designs can decrease light pollution without constraints against white LEDs. The objective of this work is to provide evidence leading to consider light pollution from a more general perspective in the benefit of humans and the environment.

This article compares two methods of roadway lighting design for situations compliant with EN 13201-2 ME/MEW series. The goal is to find out which one yields a more energy-efficient installation. The first method (further referred to as the “default” one), used by industry-standard software, assumes equally spaced luminaires (in any arrangement) and uniform width of the corresponding roadway. The second one (referred to as the “custom” one) operates on exact inventory data including spacing, road width, mounting height, and other parameters given per luminaire rather than set up globally. Both approaches are assumed to find solutions (installation setups) giving minimal energy consumption, which is accomplished, among others, by lamp dimming. The article presents the performed computations, discusses the obtained results, and analyzes the factors that might influence them. Results show that using the custom computation method and actual inventory data may bring an energy usage reduction at the level of 10% and more, compared to the default approach. Another issue critical from the practical point of view is the complexity of the solution-finding process. Although commonly known programs allow for building custom (nonuniform) scenes, the trial-and-error method of solution finding remarkably increases the design preparation time. Special heuristics embedded in the custom method allow avoiding the complexity issue and enable bulk processing, which is crucial in the case of large-scale computations made, for example, for large retrofits.

The reports presented by consulting firms show that annual energy costs generated by 340 million streetlights are expected to reach $23.9 to $42.5 billion by 2025. Those numbers reveal a motivation behind the research aiming at optimizing outdoor lighting energy efficiency. They show that even a small unit improvement can yield large benefits due to the effect of scale. The development of solid state lighting solutions enables highly effective modernization of street lighting installations. It allows obtaining power saving not only by replacing high pressure lamps with LEDs but also by improving a design quality and by introducing a dynamic street lighting control. Both methods, however, are not feasible for industry-standard software tools due to the significant complexity related to a configuration optimization, especially for large-scale projects. The goal of this article is presenting the workaround to the complexity issue, which is based on application of graph methods. They enable optimizing lighting installations in the scale of a city by providing a scalable computational environment. The presented case study shows that, thanks to applying the proposed method, one can design a lighting system which has the energy consumption reduced by up to 70%.

This article presents results of application of the customized lighting design method, carried out during the retrofit of the public lighting installations in the city of Cracow, Poland, in 2016 (completed in second half of 2016). Those results include an analysis of the power usage of new installations for which the retrofit was preceded by the customized designed. Additionally, for comparison purposes, we calculated the wattages of those installations when using standard (that is, noncustomized) power efficiency optimization. Such a standard approach could be made using any market available software (neglecting the time required for this). Analysis of working installations’ data included in the article, fully confirms theoretical predictions formulated previously on the basis of results obtained for artificial lighting situations. The main conclusion of this work is that a lighting design based on the accurate installation and road layout data, instead of uniform ones, brings substantial energy savings compared to a solution obtained using software available on the market.