| Issue |
E3S Web Conf.
Volume 470, 2023
IVth International Conference “Energy Systems Research” (ESR-2023)
|
|
|---|---|---|
| Article Number | 01044 | |
| Number of page(s) | 9 | |
| DOI | https://doi.org/10.1051/e3sconf/202347001044 | |
| Published online | 21 December 2023 | |
Assessment of the energy systems resilience using artificial intelligence methods
1
Melentiev Energy System Institute of SB RAS, AI System Department, Irkutsk, Russia
2
Fergana Polytechnic Institute, Energy Department, Fergana, Uzbekistan
* Corresponding author: massel@isem.irk.ru
Recently, in Western Europe, a direction defined by the term “Resilience” has been of great interest. Issues of energy and environmental security are of great importance in resilience research. The article discusses an approach to assessing the resilience of energy systems within the framework of the concept of situational management. It is proposed to use artificial intelligence methods: semantic (cognitive) modeling and machine learning. The choice of LSTM as a machine learning model is justified. A method for qualitative and quantitative assessment of the resilience of energy systems has been developed. An example of this method application o assess the resilience of the electric power system of the Siberian Federal District (Russia) in low-water conditions at the Angara-Yenisei cascade of hydroelectric power stations is given.
© The Authors, published by EDP Sciences, 2023
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