Data-driven fault detection and isolation in DC microgrids without prior fault data: a transfer learning approach

• Main Authors: Wang, Ting, Zhang, Chunyan, Hao, Zhiguo, Monti, Antonello, Ponci, Ferdinanda
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Electrical and electronic engineering; DC Microgrids; Current Derivatives
• Online Access: https://hdl.handle.net/10356/169004
• Institution: Nanyang Technological University

The lack of fault data is the major constraint on data-driven fault detection and isolation schemes for DC microgrids. To solve this problem, this paper develops an adversarial-based deep transfer learning model that can detect and classify short-circuit faults in DC microgrids without using histori...