DEVELOPMENT OF A MODULE FOR IDENTIFYING THE TYPE AND LOCATION OF ASYMMETRICAL SHORT CIRCUITS IN POWER TRANSMISSION LINES USING MATLAB AND NEURAL NETWORKS

The article discusses the development of a block for determining the type and location of asymmetric short circuits in 10 kV power lines using MATLAB and neural networks. The relevance of the study is due to the need to improve the reliability of distribution networks and reduce the response time to accidents. The use of artificial intelligence methods makes it possible to improve the accuracy of damage diagnosis compared to traditional approaches. The paper presents a methodology for data collection, design and training of a neural network for the analysis of emergency modes. Various types of transmission line failures were simulated in MATLAB Simulink, as well as testing of the proposed model. The results obtained confirm the effectiveness of the developed block in the localization and classification of asymmetric short circuits, which helps optimize the operation of power systems. The implementation of the proposed approach will minimize economic losses and increase the reliability of electricity supply.