This article reviews recent works applying machine learning (ML) techniques in the context of energy systems’ reliability assessment and control. We showcase both the progress achieved to date as well as the important future directions for further research, while providing an adequate background in the fields of reliability management and of ML. The objective is to foster the synergy between these two fields and speed up the practical adoption of ML techniques for energy systems reliability management. We focus on bulk electric power systems and use them as an example, but we argue that the methods, tools, etc. can be extended to other similar systems, such as distribution systems, microgrids, and multienergy systems.

中文翻译：

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能源系统可靠性管理机器学习的最新进展

本文回顾了最近在能源系统可靠性评估和控制方面应用机器学习 (ML) 技术的工作。我们展示了迄今为止取得的进展以及进一步研究的重要未来方向，同时提供了可靠性管理和机器学习领域的充分背景。目标是促进这两个领域之间的协同作用，并加快 ML 技术在能源系统可靠性管理中的实际采用。我们专注于大容量电力系统并以它们为例，但我们认为这些方法、工具等可以扩展到其他类似的系统，例如配电系统、微电网和多能源系统。