Yunfeng Jiang This email address is being protected from spambots. You need JavaScript enabled to view it.1, Lipeng Ji1, Rugang Tian1, Yang Li1, Xuanliang Yu1, and Zeqing Li1
1State Grid Xingtai Electric Power Supply Company, Xingtai 054001, China
Received: August 1, 2021 Accepted: December 16, 2021 Publication Date: January 20, 2022
Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.
Overheat of plum blossom contact is a typical fault of high voltage switchgear, which is a big hidden danger of stable operation of the power system. In this paper, the electrical thermal structural coupling simulation of plum blossom contact is realized by the finite element method, and the contact mode between contacts is constructed by combining with the conductive bridge model. The multi-physical field coupling simulation results under steady and transient conditions are given. Finally, the temperature distribution under the 1250A rated current and 40kA/5s short-circuit current is obtained, and the fault temperature is accurately predicted by random forest algorithm. The results show that the temperature rise of the contact finger area of the plum blossom contact is the most obvious, which can reach 51.93°C under the rated current and 160.27 °C under the short-circuit condition, which seriously affects the contact resistance and the deformation of the contact finger end; different working currents will affect the temperature rise characteristics of the plum blossom contact, and the matching between the plum blossom contact and the working current should be paid attention to in the actual operation. The simulation and prediction results can provide an effective reference for manufacturing and temperature prediction of plum blossom contact.
Keywords: plum blossom contact; finite element method; multi-physics coupling; random forest
REFERENCES
[1] Z. Tan, H. Zhong, Q. Xia, C. Kang, X. S. Wang, and H. Tang, (2020) “Estimating the Robust P-Q Capability of a Technical Virtual Power Plant Under Uncertainties" IEEE Transactions on Power Systems 35(6): 4285–4296. DOI: 10.1109/TPWRS.2020.2988069.
[2] T. Sun,W.Wang, S. Yang, and L. Li, (2020) “Dynamics of a High-voltage Switchgear System Excited by Earthquake" Journal of Electrical Engineering and Technology 15(2):
[3] F. Bin, F. Wang, Q. Sun, S. Chen, J. Fan, and H. Ye, (2020) “Identification of ultra-high-frequency PD signals in gas-insulated switchgear based on moment features considering electromagnetic mode" High Voltage 5(6): 688–696. DOI: 10.1049/hve.2019.0098.
[4] P. Mohseni, S. Hosseini, and M. Maalandish, (2020) “A New Soft Switching DC-DC Converter with High Voltage Gain Capability" IEEE Transactions on Industrial Electronics 67(9): 7386–7398. DOI: 10.1109/TIE.2019.2941130.
[5] H.-C. Tay and G. Swift, (1985) “On the problem of transformer overheating due to geomagnetically induced currents" IEEE Transactions on Power Apparatus and Systems PAS-104(1): 212–219. DOI: 10.1109/TPAS.1985.318916.
[6] H. Zhu, Z. Wu, C. Yang, T. Peng, Z. Chen, and X. Yang. “Fractional Steepest Ascent Method for TCU Fault Detection”. In: 51. 24. cited By 1. 2018, 1336–1342. DOI: 10.1016/j.ifacol.2018.09.561.
[7] N. A. Muhamad, A. A. Suleiman, B. Phung, and T. R. Blackburn, (2013) “Faults identification of biodegradable oil-filled transformers based on polarization and depolarization current measurement (PDC) method" IEEE Transactions on Dielectrics and Electrical Insulation 20(6): 2299–2306. DOI: 10.1109/TDEI.2013.6678883.
[8] P. Anane, Q. Huang, P. Ayimbire, and O. Bamisile, (2021) “Non-contact measurement of traveling wave of overhead transmission line" Measurement: Journal of the International Measurement Confederation 181: DOI: 10.1016/j.measurement.2021.109557.
[9] L. Huang, X. Mao, and H. Guo, (2020) “Harm Analysis of Spring Defects in Circuit Breaker Mechanical Failure" Journal of Failure Analysis and Prevention 20(3): 888–894. DOI: 10.1007/s11668-020-00889-8.
[10] M. Sattari, H. Esfahani, M. Kadkhodaei, and S. Akbarzadeh, (2021) “A mechanical contact model for superelastic shape memory alloys" Journal of Intelligent Material Systems and Structures 32(2): 208–218. DOI: 10.1177/1045389X20953617.
[11] Y. Yao, X. Ouyang, G. Zeng, Q. Tang, and W. Ma, (2021) “Research on modularizing design of 10 kV switchgear with line outlet for live maintenance" Energy Reports 7: 10–16. DOI: 10.1016/j.egyr.2021.02.033.
[12] J. Zhang, Y. Gao, and P. Hao, (2012) “Research on online high-voltage switch contact temperature rise monitoring system based on WSN" Advanced Materials Research 382: 210–214. DOI: 10.4028/www.scientific.net/AMR.382.210.
[13] J. Chen, Z. Du, D. Wang, J. Ren, and J. Ruan, (2018) “Numerical analysis of temperature field of high voltage switchgear" Advanced Technology of Electrical Engineering and Energy 37(1): 38–44.
[14] Y. Dong, M. Tang, P. Li, and J. Mao, (2019) “Transient Electromagnetic-Thermal Simulation of Dispersive Media Using DGTD Method" IEEE Transactions on Electromagnetic Compatibility 61(4): 1305–1313. DOI:10.1109/TEMC.2019.2911039.
[15] R. Han, G. Li, J. Gong, M. Zhang, and K. Zhang, (2019) “Equivalent method of joint interface based on person contact theory: Virtual material method" Materials 12(19): DOI: 10.3390/ma12193150.
[16] X. Li and D. Chen, (2005) “3-D finite element analysis and experimental investigation of electrodynamic repulsion force in molded case circuit breakers" IEEE Transactions on Components and Packaging Technologies 28(4): 877–883. DOI: 10.1109/TCAPT.2005.853175.
[17] M. Hannan, J. Ali, A. Mohamed, and M. Uddin, (2017) “A Random Forest Regression Based Space Vector PWM Inverter Controller for the Induction Motor Drive" IEEE Transactions on Industrial Electronics 64(4): 2689–2699. DOI: 10.1109/TIE.2016.2631121.
[18] C. Yang,W.Ma, J. Zhong, and Z. Zhang, (2021) “Comparative study of machine learning approaches for predicting creep behavior of polyurethane elastomer" Polymers 13(11): DOI: 10.3390/polym13111768.
[19] X. Dong, J. Dong, H. Zhou, J. Sun, and D. Tao, (2018) “Automatic Chinese Postal Address Block Location Using Proximity Descriptors and Cooperative Profit Random Forests" IEEE Transactions on Industrial Electronics 65(5): 4401–4412. DOI: 10.1109/TIE.2017.2764866.
[20] S. Ma, M. Chen, J. Wu, Y. Wang, B. Jia, and Y. Jiang, (2018) “High-voltage circuit breaker fault diagnosis using a hybrid feature transformation approach based on random forest and stacked autoencoder" IEEE Transactions on Industrial Electronics 66(12): 9777–9788.
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