A comprehensive fault detection and isolation method for DC microgrids using reduced-order unknown input observers
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 convent...
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sg-ntu-dr.10356-1727322023-12-18T06:07:11Z A comprehensive fault detection and isolation method for DC microgrids using reduced-order unknown input observers Wang, Ting Liang, Liliuyuan Hao, Zhiguo Monti, Antonello Ponci, Ferdinanda School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering DC Microgrids Fault Detection 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. This work was supported in part by the National Natural Science Foundation of China under Grant 52107124 and in part by the German Federal Ministry of Education and Research (BMBF) within the framework of Flexible Electrical Networks (FEN) Research Campus under Grant FKZ03SF0595. 2023-12-18T06:07:11Z 2023-12-18T06:07:11Z 2023 Journal Article Wang, T., Liang, L., Hao, Z., Monti, A. & Ponci, F. (2023). A comprehensive fault detection and isolation method for DC microgrids using reduced-order unknown input observers. IEEE Transactions On Power Delivery, 3274123-. https://dx.doi.org/10.1109/TPWRD.2023.3274123 0885-8977 https://hdl.handle.net/10356/172732 10.1109/TPWRD.2023.3274123 2-s2.0-85159827062 3274123 en IEEE Transactions on Power Delivery © 2023 IEEE. All rights reserved. |
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Engineering::Electrical and electronic engineering DC Microgrids Fault Detection Wang, Ting Liang, Liliuyuan Hao, Zhiguo Monti, Antonello Ponci, Ferdinanda A comprehensive fault detection and isolation method for DC microgrids using reduced-order unknown input observers |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Wang, Ting Liang, Liliuyuan Hao, Zhiguo Monti, Antonello Ponci, Ferdinanda |
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Article |
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Wang, Ting Liang, Liliuyuan Hao, Zhiguo Monti, Antonello Ponci, Ferdinanda |
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Wang, Ting |
title |
A comprehensive fault detection and isolation method for DC microgrids using reduced-order unknown input observers |
title_short |
A comprehensive fault detection and isolation method for DC microgrids using reduced-order unknown input observers |
title_full |
A comprehensive fault detection and isolation method for DC microgrids using reduced-order unknown input observers |
title_fullStr |
A comprehensive fault detection and isolation method for DC microgrids using reduced-order unknown input observers |
title_full_unstemmed |
A comprehensive fault detection and isolation method for DC microgrids using reduced-order unknown input observers |
title_sort |
comprehensive fault detection and isolation method for dc microgrids using reduced-order unknown input observers |
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2023 |
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https://hdl.handle.net/10356/172732 |
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1787136511459721216 |