A Comprehensive Fault Detection and Isolation Method for DC Microgrids Using Reduced-Order Unknown Input Observers

IEEE Transactions on Power Delivery, vol. 39, pp. 479–495

Abstract

Fault diagnosis is of critical importance to the safety of power electronic devices in dc microgrids. To detect and isolate different component faults in dc microgrids, this paper introduces a comprehensive protection scheme using reduced-order unknown input observers (ROUIOs). As opposed to conventional protection strategies, the proposed method provides a centralized fault detection and isolation (FDI) solution for dc microgrids that covers multiple faults occurring in different components in a unified process. Moreover, it reduces the complexity of observer model and relaxes the requirements of measurement signals compared with existing observer-based FDI methods for dc microgrids. To this end, the state-space model of a multi-terminal dc microgrid with different faults is first established. On this basis, a bank of ROUIOs are designed with the aim of classifying different component faults in the system. At last, the performance of the proposed FDI method is verified through numerical simulations with MATLAB/Simulink and hardware tests. Test results show that the proposed method can accurately detect and isolate different component faults in dc microgrids in a short response time of 1 ms.

Authors 5

1. Ting Wang

   Nanyang Technological University

   Affiliation as printed

   School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

2. Liliuyuan Liang

   Contemporary Amperex Technology Co., Limited.

   Affiliation as printed

   Contemporary Amperex Technology Company, Limited (CATL), Ningde, China

3. Zhiguo Hao

   Xi'an Jiaotong University

   Affiliation as printed

   School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, China

4. Antonello Monti Aachen Institute for Automation of Complex Power Systems E.ON Energy Research Center

   RWTH Aachen University

   Affiliation as printed

   Institute for Automation of Complex Power Systems, E.ON Energy Research Center, RWTH Aachen University, Aachen, Germany

5. Ferdinanda Ponci Aachen Institute for Automation of Complex Power Systems E.ON Energy Research Center

   RWTH Aachen University

   Affiliation as printed

   Institute for Automation of Complex Power Systems, E.ON Energy Research Center, RWTH Aachen University, Aachen, Germany