Improving the efficiency of street lighting electrical systems
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- Category: Content №6 2024
- Last Updated on 28 December 2024
- Published on 30 November -0001
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Authors:
O.M.Sinchuk, orcid.org/0000-0002-9078-7315, Kryvyi Rih National University, Kryvyi Rih, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
T.M.Beridze, orcid.org/0000-0003-2509-3242, Kryvyi Rih National University, Kryvyi Rih, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
O.Yu.Mykhailenko*, orcid.org/0000-0003-2898-6652, Kryvyi Rih National University, Kryvyi Rih, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
V.V.Horshkov, orcid.org/0000-0002-5129-4083, Kryvyi Rih National University, Kryvyi Rih, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
M.V.Rogoza, orcid.org/0000-0002-2395-227X, Dnipro University of Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
R.Strzelecki, orcid.org/0000-0001-9437-9450, Gdańsk University of Technology, Gdańsk, the Republic of Poland, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (6): 066 - 072
https://doi.org/10.33271/nvngu/2024-6/066
Abstract:
Purpose. To derive mathematical expressions that, using the available information, will allow forecasting the levels of electricity consumption by the city’s outdoor lighting network in the main possible scenarios for several years ahead, as well as when developing an energy-efficient smart control system for the electrotechnical complex of lighting complex.
Methodology. Creating an effective intelligent outdoor lighting control system involves the use of the following methods. First, using the empirical measurement method, information on illumination, electricity consumption, car and pedestrian traffic is obtained. Statistical methods are used to identify patterns and relationships between the measured values, as well as to make subsequent forecasts. For intelligent control of outdoor lighting, a decision-making method based on fuzzy inference is used, which allows one, based on information about the operating conditions of the outdoor lighting network, to determine the recommended value of the current or value of lighting devices and the required power source. This approach will ensure maximum system efficiency.
Findings. The obtained analytical dependencies for forecasting the electricity consumption, which are based on data from different time intervals, have determination coefficients of 66.8 and 88.1 %, respectively. The simulation of the operation of a fuzzy control system for the electricity consumption of outdoor lighting on the example of an operated part of the road operated and illuminated by ten 100 W LED lamps for summer and winter nights with different discrete control steps confirms the possibility of achieving the efficiency of outdoor lighting when using the proposed controllability option. The combined-powered control system is more efficient, reducing electricity consumption in summer and winter by more than 70 % compared to traditional control schemes.
Originality. A fuzzy control system for the electrical complex of outdoor lighting in cities is improved, which takes into account the electricity tariff in addition to the level of illumination and the car or pedestrian traffic when generating the control action for the LED driver and determining the rational power source (grid or grid/battery) for lighting devices.
Practical value. The architecture of the system for controlling electricity consumption by electrical receivers of lighting networks based on the fuzzy inference algorithm is developed, which is recommended for use to ensure an increase in the energy efficiency of this class of municipal consumers.
Keywords: street lighting, power consumption, forecasting, fuzzy control, modeling
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