Machine learning driven smart electric power systems


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Authors

  • G. Tolegenova Astana International University, L.N. Gumilyov Eurasian National University
  • A. Zakirova L.N. Gumilyov Eurasian National University
  • Zh. Akhayeva Astana International University, L.N. Gumilyov Eurasian National University
  • D. Berdymuratov M/u 01068
  • А. Syzdykov M/u 01068

DOI:

https://doi.org/10.32523/2616-7263-2022-141-4-30-37

Keywords:

intelligent network, machine learning, Internet of things, electrical network, clustering, regression

Abstract

The rapid growth of the population and economy leads to an increase in demand for electricity. Existing energy systems are intensively switching to active, flexible, and smart analogs of the smart grid, which creates big problems in many areas, such as the integration of renewable energy sources, cyberspace security, demand management, planning, and decision-making about the use of the system. Today, in the conditions of digitalization, automation, and intellectualization, traditional energy is changing, and new technologies are emerging, for example, «machine learning». This article discusses the possibilities of machine learning in electric power systems. The article describes the interrelation and interaction of elements of the smart network, the Internet of Things, and machine learning. The article presents methods of machine learning and their differences in solving technical problems of an intelligent network.

Published

2022-12-30

How to Cite

Tolegenova Г., Zakirova А., Akhayeva Ж., Berdymuratov Д., & Syzdykov А. (2022). Machine learning driven smart electric power systems. Bulletin of L.N. Gumilyov Eurasian National University Technical Science and Technology Series, 141(4), 30–37. https://doi.org/10.32523/2616-7263-2022-141-4-30-37

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