Demonstrates improved fault detection and diagnosis in microgrids, suggesting enhanced operational resilience.
The fault is caused by the periodic variation in the amplitude and phase angle of the measured impedance under the adaptive islanding operation of the microgrid. A fault differential elastic recovery technology for microgrid adaptive islanding operation is proposed, based on high-frequency measurement of the grounding electrode line and current estimation of the monitored double-circuit line. Under the quantitative feature analysis mode of high-frequency voltage mutation, a fault differential feature detection model for microgrid adaptive islanding operation is established. Through fusion analysis of the voltage distribution along the grounding electrode line under high-impedance fault conditions, the pulse injection method and the single-ended traveling wave method are combined to achieve elastic fusion for fault differentiation. A state feature monitoring model for microgrid adaptive islanding operation is constructed. Using the approach of high-frequency measurement of the grounding electrode line and current estimation of the monitored double-circuit line, the fault model parameters of microgrid adaptive islanding operation are analyzed under the influence of external interference and grounding electrode line parameters. By employing fault feature clustering, fault location, and cluster analysis methods, differential elastic recovery of faults and fault diagnosis detection are realized. Test results show that the proposed method enhances the capability for dynamic fault detection and diagnosis, effectively ensuring normal operation of the microgrid system.
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Liu et al. (2026) studied this question.
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