Short-Circuit Fault Current Parameter Prediction Method Based on Ultra-Short-Time Data Window
Abstract
:1. Introduction
2. Mathematical Model for Short-Circuit Fault
3. Short-Circuit Current Waveform Parameters Prediction Based on UDW
3.1. Prediction Principles
3.2. Algorithm Validation
4. Removal of Interference in Short-Circuit Current Signal
4.1. Principle of Trend Filtering Technique
4.2. Elimination of High-Frequency Interference and White Noise Interference of Short-Circuit Current
5. Measured Short-Circuit Current Waveform
6. Conclusions
- The UDW method has very clear advantages in fitting short-circuit current waveforms to achieve fast and accurate prediction of the waveform parameter. The exponential expressions in the UDW method fit curves closer to the actual curve, with errors of 0.15% for Ibm, 0.07% for φ1, and 0.95% for α.
- Comparing the UDW method with the modified half-wave Fourier method, it is verified that the UDW method has a shorter prediction time and higher accuracy. The improved half-wave Fourier method has a higher error when the even harmonics increase, whereas the UDW method does not have this problem, so the UDW method is more versatile and has a higher prediction accuracy. The Improved Half-Wave Fourier method calculates the steady-state and transient components separately, which results in a long calculation time, whereas the UDW method requires only 1 ms of sampled data, so the prediction time is shorter.
- Trend filtering technology can realize multiple trend filtering on the sampled data in the initial stage of prediction to achieve the purpose of quickly eliminating high-frequency interference and white noise interference, and improve the accuracy of prediction without affecting the rapidity of prediction.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Lou, Y.; Zha, Z.; Li, Z.; Wan, L. Delayed Current Zero Crossing Characteristics for Circuit Breaker Interrupting Short-Circuit Current Following Permanent Single-phase Ground Fault on Short 1000 kV AC Lines. In Proceedings of the 2019 IEEE Asia Power and Energy Engineering Conference (APEEC), Chengdu, China, 29–31 March 2019; pp. 49–54. [Google Scholar] [CrossRef]
- Wang, H.; Xu, F.; Jiao, D.; Hu, K.; Yu, L.; Zhang, Y. Analysis on the problems of three-phase short circuit current over-limited of 500 kV bus when UHV connected to Beijing power grid. In Proceedings of the 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), Xi’an, China, 25–28 October 2016; pp. 581–585. [Google Scholar] [CrossRef]
- Ye, L.; Lin, L.Z.; Juengst, K.-P. Application studies of superconducting fault current limiters in electric power systems. IEEE. Trans. Appl. Supercond. 2022, 12, 900–903. [Google Scholar] [CrossRef]
- Chae, W.; Lee, J.H.; Kim, W.H.; Hwang, S.; Kim, J.O.; Kim, J.E. Adaptive Protection Coordination Method Design of Remote Microgrid for Three-Phase Short Circuit Fault. Energies 2021, 14, 7754. [Google Scholar] [CrossRef]
- Zhang, X.H.; Sheng, S.Q.; Li, F.Q.; Hu, Y.O.; Zhang, W.C.; Pan, Y. Analysis of Limiting Measures of Three-phase Short-circuit Current of 500kV Intensive Receiving-end Power Grid in the Early Stage of UHV Construction. MATEC Web Conf. 2016, 63, 01039. [Google Scholar] [CrossRef] [Green Version]
- Chen, H.X.; Jun, W.D.; Shi, H.H. Research on Real-Time Transient Current Carrying of Overhead Transmission Lines. In Proceedings of the 2019 8th International Conference on Advanced Materials and Computer Science (ICAMCS 2019), Chongqing, China, 25–28 December 2019; pp. 367–370. [Google Scholar] [CrossRef]
- Zhao, J.Q.; LI, J.; Wu, X.C.; Men, K.; Hong, C. A novel real-time transient stability prediction method based on post-disturbance voltage trajectories. In Proceedings of the 2011 International Conference on Advanced Power System Automation and Protection (APAP 2011), Guangzhou, China, 16 October 2011; pp. 789–795. [Google Scholar]
- Ayvaz, A.; Boylu, A.B. Determination of optimal placement of fault current limiting device against short circuit faults occur in power systems. Sakarya Univ. J. Sci. 2018, 22, 615–623. [Google Scholar] [CrossRef]
- Dhara, S.; Shrivastav, A.K.; Sadhu, P.K. A fault current limiter circuit to improve transient stability in power system. Int. J. Power Electron. Drive Syst. 2016, 7, 769–780. [Google Scholar] [CrossRef] [Green Version]
- Yamaguchi, H.; Kataoka, T. Effect of Magnetic Saturation on the Current Limiting Characteristics of Transformer Type Superconducting Fault Current Limiter. IEEE Trans. Appl. Supercond. 2006, 16, 691–694. [Google Scholar] [CrossRef]
- Alam, M.S.; Abido, M.A.Y.; El-Amin, I. Fault Current Limiters in Power Systems: A Comprehensive Review. Energies 2018, 11, 1025. [Google Scholar] [CrossRef]
- Kheirollahi, R.; Zhao, S.; Lu, F. Fault Current Bypass-Based LVDC Solid-State Circuit Breakers. IEEE Trans. Power Electr. 2022, 37, 7–13. [Google Scholar] [CrossRef]
- Liu, Y.; Huang, M.; Zha, X. Short-circuit current estimation of modular multilevel converter using discrete-time modeling. IEEE Trans. Pow. Electr. 2019, 34, 40–45. [Google Scholar] [CrossRef]
- Lee, J.-I.; Dao, V.Q.; Dinh, M.-C.; Lee, S.-j.; Kim, C.S.; Park, M. Combined Operation Analysis of a Saturated Iron-Core Superconducting Fault Current Limiter and Circuit Breaker for an HVDC System Protection. Energies 2021, 14, 7993. [Google Scholar] [CrossRef]
- Roscoe, A.J.; Blair, S.M.; Dickerson, B.; Rietveld, G. Dealing with Front-End White Noise on Differentiated Measurements Such as Frequency and ROCOF in Power Systems. IEEE Trans. Instrum. Meas. 2018, 67, 2579–2591. [Google Scholar] [CrossRef] [Green Version]
- Zhang, Y.; Wang, Z.; Zhang, J. Fault detection under strong white Gaussian noise background in power systems. ICIC Express Lett. 2011, 5, 1473–1479. [Google Scholar]
- Chen, J.; Miu, X. Short circuit current peak prediction based on two-dimensional cloud model. Power Syst. Prot. Control 2018, 46, 94–101. (In Chinese) [Google Scholar]
- Wang, M.; Wei, X. Short-circuit current prediction technology based on particle swarm optimization extreme learning machine. Electr. Mach. Control 2022, 26, 68–76. (In Chinese) [Google Scholar] [CrossRef]
- Chen, L.-a. Prediction for Magnitude of Short Circuit Current in Power Distribution System Based on ANN. Intelligent Information Technology Application Association. In Proceedings of the 2011 International Symposium on Computer Science and Society(ISCCS 2011), Kota Kinabalu, Malaysia, 16 July 2011; pp. 144–147. [Google Scholar]
- Tang, L.; Miu, X.; Zhuang, S. Application of PSO-ELM in short-circuit current peak prediction of low voltage system. J. Fuzhou. Unvi. 2020, 48, 471–478. (In Chinese) [Google Scholar] [CrossRef]
- Miao, X.; Wu, X. Early Detection and prediction for short-circuit current in a multi-level low volta-ge system. Trans. China Electr. Soci. 2014, 29, 177–183. (In Chinese) [Google Scholar] [CrossRef]
- Peng, H.; Zhu, L.; Mo, W.; Wang, Y.; He, Q.; Wu, X. Zero-crossing Prediction of Short-circuit Current Using Recursive Least Square Algorithm. In Proceedings of the 2020 5th Asia Conference on Power and Electrical Engineering (ACPEE), Chengdu, China, 4–7 June 2020; pp. 1360–1364. [Google Scholar] [CrossRef]
- Chen, Q.; Zhang, G.; Liu, J.; Geng, Y.; Wang, J. Study on fast early detecting and rapid accurate fault parameters estimation method for short-circuit fault. In Proceedings of the 2017 4th International Conference on Electric Power Equipment - Switching Technology (ICEPE-ST), Xi’an, China, 22–25 October 2017; pp. 509–513. [Google Scholar] [CrossRef]
- Cao, J.; Zhao, Y.; Zhang, N.; Wang, W.; Wang, D. A research on zero-cross point forecast method of short circuit current. In Proceedings of the 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), Chongqing, China, 25–26 March 2017; pp. 2385–2389. [Google Scholar] [CrossRef]
- Yuan, Z.; Luo, C.; Fang, C.E.; Chen, S.; He, J. Design of Control System for Controlled Fault Interruption Based on Half-wave Fourier Algorithm. High Volt. Eng. 2013, 39, 869–875. [Google Scholar] [CrossRef]
- Zhang, H.J.; Wang, S.T.; Li, S.Q. Based on Wavelet Packet Feature Band Extracted Research of The Line Selection in Single-phase Ground Short Circuit. In Proceedings of the 2010 IEEE International Conference on Advanced Management Science VOL.01.Institute of Electrical and Electronics Engineers (IEEE ICAMS 2010), Chengdu, China, 9 July 2010; pp. 190–194. [Google Scholar]
- Shuin, V.A.; Dobryagina, O.A.; Shadrikova, T.Y.; Kutumov, Y.D. Protection from Single-Phase Short Circuits to Ground Based on Monitoring the Zero Sequence Capacitance in 6–10 kV Cable Networks. Power. Technol. Eng. 2021, 55, 126–135. [Google Scholar] [CrossRef]
- Ivanov, I.A.; Lyubarsky, D.R.; Rubtsov, A.A.; Tuzlukova, E.V. An Method for Determining the Amplitude of the Forced Periodic Component of the Transient Short-Circuit Current. Russ. Electr. Eng. 2021, 92, 529–534. [Google Scholar] [CrossRef]
- Julia, J.; Imme, V.B. Cramer’s rule applied to flexible systems of linear equations. Electron. J. Linear Algebra 2012, 24, 126–152. [Google Scholar] [CrossRef] [Green Version]
- Kyrchei, I. Analogs of Cramer’s rule for the minimum norm least squares solutions of some matrix equations. Appl. Math. Comput. 2012, 218, 6375–6384. [Google Scholar] [CrossRef]
Parameters | Actual Parameters | Error % | ||||
---|---|---|---|---|---|---|
n = 8 | n = 9 | n = 10 | n = 11 | n = 12 | ||
Ibm | 40 A | 5.63 | 4.40 | 0.15 | 5.12 | 6.07 |
φ1 | 90° | 3.09 | 1.73 | 0.07 | 3.44 | 5.31 |
α | 22 | 3.45 | 0.04 | 0.95 | 3.72 | 5.41 |
Parameters | Error % | |
---|---|---|
Improved Half-Wave Fourier | UDW | |
Ibm/A | 0.61 | 0.40 |
φ1/° | 2.60 | 0.07 |
α | 1.98 | 0.95 |
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Wang, M.; Wei, X.; Zhao, Z. Short-Circuit Fault Current Parameter Prediction Method Based on Ultra-Short-Time Data Window. Energies 2022, 15, 8861. https://doi.org/10.3390/en15238861
Wang M, Wei X, Zhao Z. Short-Circuit Fault Current Parameter Prediction Method Based on Ultra-Short-Time Data Window. Energies. 2022; 15(23):8861. https://doi.org/10.3390/en15238861
Chicago/Turabian StyleWang, Mengjiao, Xinlao Wei, and Zhihang Zhao. 2022. "Short-Circuit Fault Current Parameter Prediction Method Based on Ultra-Short-Time Data Window" Energies 15, no. 23: 8861. https://doi.org/10.3390/en15238861