The Use of Machine Learning in Situational Management in Relation to the Tasks of the Power Industry

Статья конференции

Massel L.V., Olga M. Gerget, Massel A.G., Timur G. Mamedov

EPJ Web Conf. International Workshop on Flexibility and Resiliency Problems of Electric Power Systems

EPJ Web Conf. Volume 217, 2019. International Workshop on Flexibility and Resiliency Problems of Electric Power Systems (FREPS 2019). P.1-6.

DOI: 10.1051/epjconf/201921701010

2019

The article discusses the application possibilities of machine learning methods (artificial neural networks (ANN) and genetic algorithms (GA) to form management actions when applying the concept of situational management for intelligent support of strategic decision-making on the development of energy. At the first stage, the application of ANN to classify extreme situations in the energy sector, to select the most effective management actions (preventive measures) in order to prevent a critical situation from developing into an emergency. Genetic algorithms are proposed to be used to determine the weighting coefficients for training ANN. Analgorithm for constructing a classifier based on a neural network and a demonstration task using data on generation and consumption of the United Electric Power System of Siberia are presented

Библиографическая ссылка

Massel L.V., Olga M. Gerget, Massel A.G., Timur G. Mamedov The Use of Machine Learning in Situational Management in Relation to the Tasks of the Power Industry // EPJ Web Conf. Volume 217, 2019. International Workshop on Flexibility and Resiliency Problems of Electric Power Systems (FREPS 2019). P.1-6. DOI: 10.1051/epjconf/201921701010 https://www.epj-conferences.org/articles/epjconf/abs/2019/22/epjconf_freps18_01010/ epjconf_freps18_01010.html

situational management