Influence of the Inverse-Time Protection Relays on the Voltage Dip Index

doi:10.1007/s12204-014-1509-3

Abstract

Abstract: The probability-assessment analyses on the characteristic value of voltage dip by using Monte Carlo stochastic modeling method to stimulate the randomness of the short circuit fault are introduced. Using Matlab and Power Systems CAD (PSCAD), we design control interface which combines the electromagnetic transient simulation with the Monte Carlo method. Specifically, the designing of interface which is meant to employ the method of Matlab programming to control the electromagnetic transients including direct current (EMTDC) simulation is introduced. Furthermore, the influences of the protection devices on the voltage dip to ensure the authenticity and the referential reliability are simulated. A system with the inverse-time protection devices equipped on each line which can coordinate together is designed to cut off the short-circuit fault. The voltage dip of the designed system is assessed by the pre- and post-system average root mean square (RMS) variation frequency index, and the voltage dip index is compared with the Information Technology Industry Council (ITIC) curves. The simulation results demonstrate that the inverse-time relay protection equipments are well-coordinated, and the severity and the range of the voltage dip are influenced by the cooperation of the equipped inverse-time protection devices.

Key words: power quality| voltage dip| inverse-time protection relay| Monte Carlo algorithm| simulation

摘要： The probability-assessment analyses on the characteristic value of voltage dip by using Monte Carlo stochastic modeling method to stimulate the randomness of the short circuit fault are introduced. Using Matlab and Power Systems CAD (PSCAD), we design control interface which combines the electromagnetic transient simulation with the Monte Carlo method. Specifically, the designing of interface which is meant to employ the method of Matlab programming to control the electromagnetic transients including direct current (EMTDC) simulation is introduced. Furthermore, the influences of the protection devices on the voltage dip to ensure the authenticity and the referential reliability are simulated. A system with the inverse-time protection devices equipped on each line which can coordinate together is designed to cut off the short-circuit fault. The voltage dip of the designed system is assessed by the pre- and post-system average root mean square (RMS) variation frequency index, and the voltage dip index is compared with the Information Technology Industry Council (ITIC) curves. The simulation results demonstrate that the inverse-time relay protection equipments are well-coordinated, and the severity and the range of the voltage dip are influenced by the cooperation of the equipped inverse-time protection devices.

关键词: power quality| voltage dip| inverse-time protection relay| Monte Carlo algorithm| simulation

CLC Number:

TM 774

GAO Xin-ke1,2* (高新科), LIU Ya-peng3 (刘玡朋). Influence of the Inverse-Time Protection Relays on the Voltage Dip Index[J]. Journal of shanghai Jiaotong University (Science), 2014, 19(3): 354-360.

References

[1] Honrubia-Escribano A, G′omez-Lazaro E,Molina-Garcia A, et al. Influence of voltage dips on industrial equipment: Analysis and assessment [J].International Journal of Electrical Power & Energy Systems, 2012, 41(1): 87-95.
[2] Ai Q, Zhou Y G, Xu W H. Adaline and its application in power quality disturbances detection and frequency tracking [J]. Electric Power Systems Research,2007, 77(5): 462-469.
[3] Jin Z J, Wang F H, Zhu Z S. Application of extended Kalman filter to the modeling of electric arc furnace for power quality issues [J]. Journal of Shanghai Jiaotong University (Science), 2007, 12(2): 257-262.
[4] Wang C, Cheng H Z, Hu Z C, et al. Distribution system optimization planning based on plant growth simulation algorithm [J]. Journal of Shanghai Jiaotong University (Science), 2008, 13(4): 462-467.
[5] Won D J, Ahn S J, Moon S I. A modified sag characterization using voltage tolerance curve for power quality diagnosis [J]. IEEE Transactions on Power Delivery,2005, 20(4): 2638-2643.
[6] Martinez J A, Martin-Arnedo J. Voltage sag stochastic prediction using an electromagnetic transients program [J]. IEEE Transactions on Power Delivery,2004, 19(4): 1975-1982.
[7] Song Yun-ting, Guo Yong-ji, Zhang Rui-hua. Probabilistic assessment of voltage sags and momentary interruption based on MONTE-CARLO simulation [J].Automation of Electric Power Systems, 2003, 27(18):47-51 (in Chinese).
[8] Martinez J A, Martin-Arnedo J. Voltage sag analysis using an electromagnetic transients program [C]//Proceedings of Power Engineering Society Winter Meeting. [s.l.]: IEEE, 2002: 1135-1140
[9] Martinez J A, Martin-Arnedo J. Voltage sag studies in distribution networks. Part I. System modeling[J]. IEEE Transactions on Power Delivery, 2006,21(3): 1670-1678.
[10] Martinez J A, Martin-Arnedo J. Voltage sag studies in distribution networks. Part II. Voltage sag assessment[J]. IEEE Transactions on Power Delivery, 2006,21(3): 1679-1688.
[11] Martinez J A, Martin-Arnedo J. Voltage sag studies in distribution networks. Part III. Voltage sag index calculation [J]. IEEE Transactions on Power Delivery,2006, 21(3): 1689-1697.
[12] Benmouyal G, Meisinger M, Burnworth J, et al.IEEE standard inverse-time characteristic equations for overcurrent relays [J]. IEEE Transactions on Power Delivery, 1999, 14(3): 868-872.
[13] Tan J C,Mclaren PG, JayasingheR P, et al. Software model for inverse time overcurrent relays incorporating IEC and IEEE standard curves [C]//Proceedings of the 2002 IEEE Canadian Conference on Electrical & Computer Engineering. [s.l.]: IEEE, 2002: 37-41.
[14] BS EN 61000-4-11(2004), Electromagnetic compatibility (EMC) testing and measurement techniques, voltage dips, short interruptions and voltage variations immunity tests [S].
[15] Urdaneta A J, Restrepo H, M′arquez S, et al. Coordination of directional overcurrent relay timing using linear programming [J]. IEEE Transactions on Power Delivery, 1996, 11(1): 122-129.
[16] Wang J, Chen S, Lie T T. System voltage sag performance estimation [J]. IEEE Transactions on Power Delivery, 2005, 20(2): 1738-1747.
[17] Gupta C P, Milanovic J V. Probabilistic assessment of equipment trips due to voltage sags [J]. IEEE Transactions on Power Delivery, 2006, 21(2): 711-718.
[18] Aung M T, Milanovic J V. Stochastic prediction of voltage sags by considering the probability of the failure of the protection system [J]. IEEE Transactions on Power Delivery, 2006, 21(1): 322-329.
[19] Xiao Xiang-ning, Tao Shun. Voltage sags types under different grounding modes of neutral and their propagation:Part I [J]. Transactions of China Electrotechnical Society, 2007, 22(9): 143-153 (in Chinese).