Liudmila V. Massel, Aleksei G. Massel, Timur G. Mamedov, Daria A. Gaskova, Aleksey R. Tsybikov, Nikita I. Shchukin

Melentiev Energy Systems Institute SB RAS

Recently, the direction defined by the term “Resilience” has been of great interest abroad. Research of Russian scientists in this area is conducted mainly in the field of technical sustainability as one of resilience aspect, while Western Europe scientists consider this area more broadly and include environmental, psychological, social and economic resilience. Energy and environmental security issues are of great importance in resilience studies. The article considers an approach to assessing the resilience of energy systems within the framework of the situational management concept. The justification of the need for the use of machine learning methods is given and an example of the use of these methods for the quantitative assessment of resilience is also given

energy systems resilience, situational management, LSTM, parameters prediction, energy sector