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- Title
Short-Circuit Fault Current Parameter Prediction Method Based on Ultra-Short-Time Data Window.
- Authors
Wang, Mengjiao; Wei, Xinlao; Zhao, Zhihang
- Abstract
The prediction of short-circuit current parameters is essential for the adoption of short-circuit fault limiting techniques and the reliable cut-off of circuit breakers. In order to quickly and accurately predict the short-circuit current waveform parameters, a short-circuit fault current prediction method based on ultra-short-time data windows (UDWs) is proposed. First, a mathematical model for describing short-circuit faults is constructed and the characteristics of short-circuit currents are analyzed. Then, the principle of the UDW method for predicting short-circuit current waveform parameters is derived, the correctness of the principle is verified by setting-up an ideal signal through simulation, and the exponential and linear expressions fitted to the curve are analyzed and compared with the improved half-wave Fourier method for predicting current parameters. Finally, trend filtering technology is proposed to eliminate high-frequency interference and white noise interference. The results show that the ultra-short-time data window method can quickly and accurately predict the short-circuit current waveform parameters, where the exponential expression is a better fit to the waveform, and the trend filtering technique enables the elimination of high-frequency and white noise interference in the initial stages of prediction.
- Subjects
SHORT-circuit currents; FAULT currents; WHITE noise; SEPARATION of variables; DATABASES; PHOTOVOLTAIC effect
- Publication
Energies (19961073), 2022, Vol 15, Issue 23, p8861
- ISSN
1996-1073
- Publication type
Article
- DOI
10.3390/en15238861