Improving the recognition of power supply systems operation modes based on the methods of machine learning
The article analyzes the prospects of applying methods based on multiple simulation, statistical processing of the results of model experiments and machine learning in relay protection and automation of electrical networks. New methods are proposed for combining logical signals from various triggering elements of a multidimensional relay protection device to increase the reliability and recognizability of normal and emergency modes of power system operation using an artificial neural network and the decision tree method. The parameters of actuation of five separate onedimensional launching elements were determined according to the Bayesian criterion for minimizing the average risk.