Economic Impact of Intelligent Dynamic Control in Urban Outdoor Lighting

Abstract-In this paper, the problem of short-term prediction of traffic flow in a city traffic network is considered. This prediction is performed in order to provide input data to a dynamic control system for street lighting. The forecasting is done by a multi-layer using artificial neural network. Because of the limited number of sensors, the data is insufficient to describe the relation between the traffic intensity at a given point and the points in which the flow intensity is measured. The proposed approach is tested by using data from the centre of Kraków. The prediction error turned to be low.

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“…Outdoor lighting optimisation can have a significant impact on economy [15]. As mentioned in the introduction, it is due to two factors.…”

Section: Motivationmentioning

confidence: 99%

“…There have been multiple experiments and assessments conducted so far. These include highway lighting [16], tunnels [17] and urban areas [15], [18]. However, there still is much room for improvement.…”

Section: Motivationmentioning

confidence: 99%

Prediction of Traffic Intensity for Dynamic Street Lighting

Bielecka

Bielecki

Ernst

et al. 2017

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

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“…As noted by Wojnicki, Ernst and Kotulski [34], methods of obtaining energy from renewable resources are well-studied and under constant improvement. Yet reduction of power consumption is the other main factor contributing to improvement of sustainability.…”

Section: Energy Plus Knowledge Equals Smart Utilities and Smart Citiementioning

confidence: 99%

Future of Humanity: Energy and Knowledge Engineering

Aktas¹

2017

csit

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Energy has become the keyword relevant to the economic and social development and sustainability of all countries as well as the ecological future of the world. Knowledge-based strategic planning and decisions in energy are therefore very crucial for all. Knowledge may be defined as the information needed for good planning and intelligent decisions for any human being, from a lay man to a top man in a public or private organization up to even the country president. In the article, after some introductory remarks about energy and knowledge, knowledge -energy relation is defined. Smart cities and intelligent utilities / smart energy, Energy Engineering and Knowledge Engineering terms are also elaborated. As a conclusion, the synergy and even a symbiosis between energy and knowledge is noted and it is stated that energy engineering and knowledge engineering together with nano science and technology will be very crucial for the future of humanity.

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“…Street lighting is a representative example of applying smart city concepts, increasing safety and sustainability by adjusting lighting levels to particular needs [2,3,8]. Depending on the light source technology, control availability and actual area under consideration, being either highways or urban areas, different levels of energy consumption reduction can be achieved.…”

Section: Related Researchmentioning

confidence: 99%

“…Data comes from standalone sensor systems and Internet-of-Things (IoT) devices [5][6][7]. Some of the main drivers are safety, quality of life and sustainability, including electric energy savings [2,8]. The smart city concepts can be applied at different scales.…”

Section: Related Researchmentioning

confidence: 99%

Empirical Study of How Traffic Intensity Detector Parameters Influence Dynamic Street Lighting Energy Consumption: A Case Study in Krakow, Poland

Wojnicki

Kotulski

2018

Sustainability

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Abstract:The deployment of dynamic street lighting, which adjusts lighting levels to fulfill particular needs, leads to energy savings. These savings contribute to the overall lighting infrastructure maintenance cost. Yet another contribution is the cost of traffic intensity data. The data is read directly from sensor systems or intelligent transportation systems (ITSs). The more frequent the readings are, the more costly they become, because of hardware capabilities, data transfer and software license costs, among others. The paper investigates a relationship between the frequency of readings, in particular the averaging window size and step, and achieved energy savings. It is based on a simulation, taking into account a representative part of a city and traffic intensity data, which span over a period of one year. While the energy consumption reduction is simulated, all data, including each luminaire power setting, induction loop locations and street characteristics, come from a representative sample of the city of Krakow, Poland. Controlling the power settings complies with the lighting standard CEN/TR 13201. Analysis of the outcomes indicates that the shorter the window size or step are, the more energy saving that is available. In particular, for the previous standard CEN/TR 13201 2004, having the window size and step at 15 min results in 26.75% of energy saving, while reducing these values to 6 min provides 27%. Savings are more profound for the current standard (CEN/TR 13201 2014), assuming a 15 min size and step results in 47.43%, while having a 6 min size and step provides 47.69%. The results can serve as a guideline for identifying the economic viability of dynamic lighting control systems. Additionally, it can be observed that the current lighting standard provides far greater potential for dynamic control then the previous standard.

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Economic Impact of Intelligent Dynamic Control in Urban Outdoor Lighting

Cited by 31 publications

References 6 publications

Prediction of Traffic Intensity for Dynamic Street Lighting

Prediction of Traffic Intensity for Dynamic Street Lighting

Future of Humanity: Energy and Knowledge Engineering

Empirical Study of How Traffic Intensity Detector Parameters Influence Dynamic Street Lighting Energy Consumption: A Case Study in Krakow, Poland

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