The paper investigates the application of solar energy in public lighting for realizing a street lighting sub-grid with positive yearly energy balance. The focus is given to the central controller, which ensures the adaptive behavior of the overall system and provides smart city services to the end users via its web-based user interface. A functionality of the controller of special interest is the optimization of the energy management of the system, i.e., determinin. The paper investigates the application of solar energy in public lighting for realizing a street lighting sub-grid with positive yearly energy balance. The focus is given to the central controller, which ensures the adaptive behavior of the overall system and provides smart city services to the end users via its web-based user interface. A functionality of the controller of special interest is the optimization of the energy management of the system, i.e., determining when to sell and buy electricity to/from the grid, in order to minimize the cost of electricity (or to maximize the profit) subject to a given, time-of-use variable energy tariff. This requires precise forecasts of the energy produced and consumed, as well as appropriate robust optimization techniques that guarantee that the system bridges potential power outages of moderate duration in island mode. The algorithms implemented in the controller are presented in detail, together with the evaluation of the operation of a deployed physical prototype with 191 luminaries over a horizon of six months, based on the monitoring data collected by the proposed controller.••••System architecture is proposed for energy-positive solar street lighting.••Intelligent control is advised for adaptation to environmental conditions.••Methods for forecasting and optimizing the energy flow are presented.••Operation of a physical prototype with 191 luminaries is evaluated.Street lightingRenewable energyEnergy managementSmart citiesThis research has been motivated by the application of solar energy in public lighting with the intention to achieve an energy-positive street lighting sub-grid, briefly named E + grid. The proposed system architecture exploits all of the four possible approaches defined in Ref. to minimize the energy consumption and the operating costs of the lighting system: advances in technology (i) by applying energy-efficient LED luminaries, photovoltaic (PV) panels for energy production, and batteries for intermediate energy storage; changes in use patterns (ii) by adjusting the daily switch on/off times to current meteorological conditions; modification in the basis of design (iii) by applying adaptive lighting that concentrates the lighting service to locations and times with vehicle or pedestrian traffic; and finally, changes in contracts (iv) by optimizing the energy management of the system subject to a time-of-use variable energy tariff. Hence, the proposed system can fully unfold its benefits if deployed in areas with low traffic during the night, such as residential areas, industrial parks, or supermarket car parks. To the best of our knowledge, the proposed system is the first in the literature to integrate all these technologies in a single street lighting system.This paper focuses on the central controller (CC) of the E + grid system that ensures the adaptation of the lighting system to the actual environmental cond. A recent review on the opportunities and challenges in solid-state lighting, including technological development, policy options, environmental impact, as well as future trends, is presented in Ref. The potential approaches to reducing the energy consumption of street lighting systems, such as changes in technology (e.g., light sources), in use patterns (e.g., applying a twilight switch and remote dimming), and changes to standards and design criteria have been investigated in Refs.,. These trends and the applicable technological solutions are review in detail below.Adaptive lighting, i.e., the adjusting of the intensity and the distribution of light to the environmental conditions and user behavior, received significant attention recently, due to the favorable dimming performance of LED light sources. An optimization approach to balancing light quality and energy efficiency in color turnable adaptive lighting systems is proposed in Refs., whereas the psychological effects of adaptive lighting have been studied by Haans and de Kort. Pizzuti et al. proposed reducing the energy consumption of street lighting by adjusting the dimming levels to the forecasted traffic intensity, and using an ensemble of artificial neural networks (ANNs) to derive such a forecast.Various.
