Identification of pre-emergency states in the electric power system on the basis of machine learning technologies
The paper proposes a concept of an intelligent system for early detection of pre-emergency state in electric power system as an option of preventive operation and emergency control. The main goal of such a system is to early warn and prevent dangerous states and emergency situations before they lead to a system blackout. Consideration is given to a construction principle of systems for security monitoring and assessment on the basis of machine learning algorithms. The feasibility of the approach in a proof-of-concept has been demonstrated on the modified 53-node reliability test system (IEEE RTS-96) and IEEE 118 power system. © 2016 IEEE.
Библиографическая ссылка
Kurbatsky V., Tomin N. Identification of pre-emergency states in the electric power system on the basis of machine learning technologies // Proceedings of the World Congress on Intelligent Control and Automation (WCICA). 2016. P.378-383. ISBN (print): 9 781 467 . DOI: 10.1109/WCICA.2016.7578291
