Intelligent monitoring and forecasting of the expected operating conditions of electric power system

One of the most important problems in the modern power industry of focus is the organization intelligent monitoring conditions and their control with the use of new forecasting methods, especially methods of artificial intelligence. The paper presents original intelligent methods and approaches to solve the problems of monitoring and forecasting of the expected EPS operating conditions, namely: the hybrid approach to short-term forecasting of the expected state variables on the basis of combined application of artificial neural networks and Hilbert-Huang transform and the approach to monitoring and forecasting of heavy load and/or emergency conditions on the basis of modern methods of adaptive clustering and factor analysis.