Power electronics anomaly detection and diagnosis with machine learning and deep learning methods: A survey

Abstract

Power electronics pertains to the conception, regulation, and utilization of electronic power circuits to proficiently administer and transform electrical energy. Power electronics play a crucial role in maintaining the reliability, efficiency, and security of complex production systems. Also, increasingly important in various applications such as renewable energy systems, electric vehicles, and industrial automation. However, modern power electronics systems are vulnerable to both cyber and physical anomalies due to the integration of information and communication technologies. So far, different methods have been used to detect abnormalities. This survey provides an overview of the state-of-the-art in anomaly detection in power electronics using machine learning and deep learning methods. It highlights the potential of these techniques in addressing the growing complexity and vulnerability of power electronics systems.