Machine learning (ML) has become a rising sophisticated technological application trend in the electrical industry in recent years. Such innovation provides optional methodologies for many existing applications, such as power and load profile forecasting, reliability evaluation, substation behavior detection and state observation of electrical equipment, and so on. This paper presents a review of various supervised and unsupervised ML techniques and applications for electrical power systems, including generation, transmission, distribution and micro-grid. The algorithms and applications are mainly summarized from IEEE journals and the interest of this paper shows the roles and developments of most used algorithms and its corresponding extensions and performance in different applications. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

中文翻译：

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电力系统有监督和无监督学习技术综述：算法与应用

近年来，机器学习 (ML) 已成为电气行业日益成熟的技术应用趋势。这种创新为许多现有应用提供了可选方法，例如功率和负载曲线预测、可靠性评估、变电站行为检测和电气设备状态观察等。本文综述了电力系统（包括发电、输电、配电和微电网）的各种有监督和无监督机器学习技术和应用。算法和应用主要来自IEEE期刊，本文的兴趣展示了最常用算法的作用和发展及其在不同应用中的相应扩展和性能。© 2021 日本电气工程师学会。