Recent Developments in Machine Learning for Energy Systems Reliability Management

Abstract

This paper reviews recent works applying machine learning 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 machine learning. The objective is to foster the synergy between these two fields and speed up the practical adoption of machine learning 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, micro-grids, and multi-energy systems.

An Overview of Artificial Intelligence Applications for Power Electronics

“…Maintenance [18] in power electronics is a topic that includes reliability, condition monitoring, remaining useful life prediction, etc. Several review papers in the last decade can be found in [19]- [22]. In [19], a state-of-the-art analysis of the condition monitoring and fault detection in power electronics is presented.…”

“…This paper only discusses the category of AI algorithms in the PHM area, while there is no algorithm detail or comparative analysis. In [22], machine learning methods applied in reliability management of energy systems are summarized. It focuses on the machine learning method and the maintenance task only.…”

An overview of artificial intelligence applications for power electronics

“…Maintenance [18] in power electronics is a topic that includes reliability, condition monitoring, remaining useful life prediction, etc. Several review papers in the last decade can be found in [19][20][21][22]. In [19], a state-of-the-art analysis of the condition monitoring and the fault detection in power electronics is presented.…”

“…This paper focuses on the category of AI algorithms in PHM without any specific details. In [22], machine learning methods applied in reliability management of energy systems are summarized. It focuses on the machine learning methods and the maintenance tasks only.…”

Machine learning for ranking day-ahead decisions in the context of short-term operation planning

“…More recently, due to the advances in the field of machine learning, an increasing number of papers exploiting this approach have been published (see, for example [6]- [9]). We refer the interested reader to [10] for a comprehensive survey of recent works applying machine learning in the context of reliability management. Closer to the subject of the present work, several papers propose to use machine learning to learn the outputs of a SCOPF.…”