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April 2015, № 4 (179)

Semenova N.G., Valiullin K.R. INTELLIGENT ENERGY-EFFICIENT STREET LIGHTING CONTROL SYSTEM BASED ON NEURAL NETWORK TECHNOLOGY Street lighting systems in modern cities are complex high power consuming facilities and development of energy-saving control systems is required for their effective work. Comparative analysis of existing methods of street lighting control, shows that in a modern city, they cannot work effectively. So, the development of intelligent control systems that simultaneously measure, analyze, and reduce power consumption, providing the flexibility in condition of uncertain data is important and relevant nowadays. Because of the many random factors, such as weather conditions, changes in the length of day light and others formalization of the power of the lighting installation relation from the ambient light is difficult. For the approximation of this function is proposed to use the neural networks, which was chose because of their efficiency in the field of approximation of continuous functions. Algorithm of intelligent street lighting control system with training based on the back propagation was developed and implemented in software. Developed control system operates in two modes: mode of training a neural network; control of a lighting system. Features of the program are: changing of the target luminance value of road surface; receiving of training sample directly in the process of lighting system control and preservation of training samples in tabular form for further processing. The program developed by the authors tested on experimentally installation consisting of five LED-lamp models of street lighting. The results of the experiments showed that the efficiency of the intellectual system of street lighting control compared with traditional amounted to 6.3 %.Key words: street lighting, control system, neural network technology, energy efficiency.


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About this article

Author: Semenova N.G.

Year: 2015

Sergey Aleksandrovich

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