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

• المؤلفون الرئيسيون: Wang, Ting, Zhang, Chunyan, Hao, Zhiguo, Monti, Antonello, Ponci, Ferdinanda
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Electrical and electronic engineering; DC Microgrids; Current Derivatives
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/169004
• المؤسسة: 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...