مقاله انگلیسی تشخیص خطای ریزشبکه DC با تحلیل چند وضوحی امواج در حال حرکت
Abstract
Keywords
Introduction
Preliminaries on TW theory
DWT and MRA
High-frequency fault signatures in a DC system
Fault classification and location scheme
Performance verification
Conclusion
CRediT authorship contribution statement
Declaration of Competing Interest
Acknowledgment
References
ABSTRACT
Fast detection and isolation of faults in a DC microgrid is of particular importance. Fast tripping protection (i) increases the lifetime of power electronics (PE) switches by avoiding high fault current magnitudes and (ii) enhances the controllability of PE converters. This paper proposes a traveling wave (TW) based scheme for fast tripping protection of DC microgrids. The proposed scheme utilizes a discrete wavelet transform (DWT) to calculate the high-frequency components of DC fault currents. Multiresolution analysis (MRA) using DWT is utilized to detect TW components for different frequency ranges. The Parseval energy of the MRA coefficients are then calculated to demonstrate a quantitative relationship between the fault current signal energy and coefficients’ energy. The calculated Parseval energy values are used to train a Support Vector Machine classifier to identify the fault type and a Gaussian Process regression engine to estimate the fault location on the DC cables. The proposed approach is verified by simulating two microgrid test systems in PSCAD/EMTDC.