Controlled Fault Current Interruption Scheme for Improved Fault Prediction Accuracy
To enhance the accuracy and efficiency of controlled fault current interruption (CFI) in short-circuit current processing within power systems, a half-cycle elimination prediction algorithm and a double-sampling CFI sequence method are proposed in this study. By analyzing the non-periodic and period...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/6/3106 |
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| Summary: | To enhance the accuracy and efficiency of controlled fault current interruption (CFI) in short-circuit current processing within power systems, a half-cycle elimination prediction algorithm and a double-sampling CFI sequence method are proposed in this study. By analyzing the non-periodic and periodic components of short-circuit currents, the half-cycle elimination method and fast Fourier transform are utilized to compute these two components, respectively. The double-sampling CFI sequence approach is designed to fully utilize the response and waiting times of relay protection. Following the first sampling to estimate the target zero-crossing point, the remaining response and waiting times are allocated for a second sampling and recalculation to enhance the precision of zero-crossing prediction. MATLAB R2023a is employed to conduct multi-scenario simulations, and the algorithm’s performance is evaluated using actual recorded waveform data. The results demonstrate that the proposed algorithm accurately predicts the target zero-crossing point after a short circuit, with a computational error of less than 0.2 ms. Furthermore, the double-sampling sequence method is shown to improve the accuracy of open-circuit zero-crossing point calculations by an order of magnitude. This work provides a novel technical approach for the fast and precise handling of short-circuit faults in power systems. |
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| ISSN: | 2076-3417 |