机器学习驱动的智能电力系统

G. Tolegenova, A. Zakirova, Zh.B. Akhayeva, D. Berdymuratov, А. Syzdykov
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引用次数: 0

摘要

人口和经济的快速增长导致电力需求的增加。现有的能源系统正在密集地转向主动、灵活和智能的智能电网,这在许多领域产生了大问题,例如可再生能源的整合、网络空间安全、需求管理、规划和系统使用决策。今天,在数字化、自动化和智能化的条件下,传统能源正在发生变化,“机器学习”等新技术正在兴起。本文讨论了电力系统中机器学习的可能性。本文描述了智能网络、物联网和机器学习要素之间的相互关系和相互作用。本文介绍了机器学习的方法及其在解决智能网络技术问题中的区别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning driven smart electric power systems
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.
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