Research Progress on the Application of Machine Learning in Power System Security

Abstract

Machine learning is considered to be an emerging technology that can be widely used. The construction of power system has always been an important field of social livelihood security and development in China. In recent years, the application of machine learning in power system security has also made great progress in the environment of increasing attention to the research on the intersection and integration of machine learning and various disciplines. According to the latest progress, the application of machine learning in this field is mainly divided into hardware layer and software layer. The research on security guarantee of hardware layer mainly focuses on the prediction and evaluation of transient stability and load forecasting, while the research on software layer mainly focuses on network attack detection, and most of the research focuses on model and method innovation. Using machine learning to quickly evaluate and predict the operation state of power system, so as to realize in-depth analysis and facilitate the operation and maintenance personnel to make appropriate human intervention, which can represent the current research trend of machine learning in the field of power system security.