A Model-Based Series Arc Fault Detection Method for Multiterminal DC Microgrids

IEEE Transactions on Power Electronics, vol. 41, pp. 2263–2277

Abstract

Timely and accurate detection of series arc faults in multi-terminal DC microgrids is a challenging task. Existing series arc fault detection methods suffer from different deficiencies in terms of selectivity, applicability and efficiency. To solve these problems, this paper introduces a model-based series arc fault detection scheme for DC microgrids. First, a minimized system model dedicated to series arc fault detection is derived. On this basis, a bank of reduced-order unknown input observers are established. Through recognizing predefined patterns in the output of the observer bank, various series arc faults can be detected and isolated in a timely manner. The proposed method is advantageous in that it can simultaneously locate multiple series arc faults in complex DC microgrids without relying on auxiliary power hardware, special measurement devices, prior fault data, and avoid cumbersome threshold settings. The performance of the proposed method has been verified through numerical simulations with MATLAB/Simulink and experimental tests.

Authors 3

1. Zhiguo Hao

   Xi'an Jiaotong University

   Affiliation as printed

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

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

2. 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

3. 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