Short-Circuit Fault Current Parameter Prediction Method Based on Ultra-Short-Time Data Window

Autor: Mengjiao Wang, Xinlao Wei, Zhihang Zhao
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Energies, Vol 15, Iss 23, p 8861 (2022)
Druh dokumentu: article
ISSN: 1996-1073
DOI: 10.3390/en15238861
Popis: 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.
Databáze: Directory of Open Access Journals
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