Analysis and Development of an Algorithm to increase the Energy Efficiency of Electrical Street Lighting Systems Using an Artificial Neural Network

The purpose of this paper is to improve the energy efficiency of electric street lighting systems by developing methods for optimizing the parameters of its elements and energy-efficient control algorithms. To achieve this, an analysis of existing technical solutions and justification of the system of indicators was made; methods have been developed to optimize the parameters of the elements of the street network during its design or modernization. An algorithm for adjusting the power of street lighting installations using a neural network for predicting traffic intensity and an integrative algorithm for determining energy-efficient operation through two variables are proposed, combining the algorithms for selecting power according to the value of natural light and adjusting the mode of operation according to the traffic. A simulation model has been developed for the functioning of the street lighting electrical system, taking into account external influences. The training of the neural network was performed in the MATLab environment.