1. bookVolume 12 (2012): Issue 6 (December 2012)
Journal Details
License
Format
Journal
eISSN
1335-8871
First Published
07 Mar 2008
Publication timeframe
6 times per year
Languages
English
Open Access

Approximate Entropy Based Fault Localization and Fault Type Recognition for Non-solidly Earthed Network

Published Online: 15 Dec 2012
Volume & Issue: Volume 12 (2012) - Issue 6 (December 2012)
Page range: 309 - 313
Journal Details
License
Format
Journal
eISSN
1335-8871
First Published
07 Mar 2008
Publication timeframe
6 times per year
Languages
English

For non-solidly earthed network, the fault localization of single phase grounding fault has been a problem. A novel fault localization and fault type recognition method of single phase grounding fault based on approximate entropy is presented. The approximate entropies of transient zero sequence current at both ends of healthy section are approximately equal, and the ratio is close to 1. On the contrary, the approximate entropies at both ends of fault section are different, and the ratio is far from 1. So, the fault section is located. At the same fault section, the smaller is the fault resistance, the larger is the approximate entropy of transient zero sequence current. According to the function between approximate entropy and fault resistance, the fault type is determined. The method has the advantages of transferring less data and unneeded synchronous sampling accurately. The simulation results show that the proposed method is feasible and accurate.

Keywords

[1] Summer, J.H. (1948). Theory and operation of Peterson coils. Journal of the Institution of ElectricalEngineers - Part II: Power Engineering, 94 (40), 283-298.Search in Google Scholar

[2] Zhang, L., Yang, Y.H., Si, D.M. (2008). Distribution network fault localization based on the zero sequence current and magnetic field detection spot. Automationof Electric Power Systems, 32 (14), 73-76.Search in Google Scholar

[3] Zhang, L., Yang, Y.H., Yang, X.Y. (2009). Method of mobile phase-comparison for fault location of distribution network. Proceedings of the CSEE, 29 (7), 91-97.Search in Google Scholar

[4] Pan, Z.C., Zhang, H.F., Zhang, F. (2007). Analysis and modification of signal injection based fault line selection protection. Automation of Electric PowerSystems, 31(4), 71-75.Search in Google Scholar

[5] Jia, H.B., Zhao, H.F., Fang, Q.H. (2012). A singlephase earth fault location method for distribution network based on multi-terminal traveling wave. Automation of Electric Power Systems, 36 (2), 96-100.Search in Google Scholar

[6] Song, G.B., Li, G., Yu, Y.Y. (2011). Single-phase earth fault section location based on phase current fault component in distribution network. Automation ofElectric Power Systems, 35 (21), 84-90.Search in Google Scholar

[7] Ni, G.K., Bao, H., Zhang, L. (2010). Criterion based on the fault component of zero sequence current for online fault location of single-phase fault in distribution network. Proceedings of the CSEE, 30 (31), 118-112.Search in Google Scholar

[8] Wang, X.W., Tian, S., Zhang, Z. (2011). A novel method of fault location for distribution network. In International Conference on Advanced Power SystemAutomation and Protection, 16-20 October 2011. IEEE, 1525-1528.10.1109/APAP.2011.6180746Search in Google Scholar

[9] Lan, H., Ai, T., Zhang, G.L. (2009). Single-phase adaptive reclosure of transmission lines based on EMD and approximate entropy. Power System Technology, 33 (20), 211-214.10.1109/ICIECS.2009.5364638Search in Google Scholar

[10] He, W., Chen, X., Yang, J.H. (2005). Classification of EEG signal based on approximate entropy. Journal ofBiomedical Engineering Research, 23 (4), 211-214.Search in Google Scholar

[11] He, W.P., He, T., Cheng, H.Y. (2011). A new method to detect abrupt change based on approximate entropy. Acta Physica Sinica, 60 (4), 0492021-9.Search in Google Scholar

[12] Pinheiro, E., Postolache, O., Girao, P. (2010). Nonintrusive device for real-time circulatory system assessment with advanced signal processing capabilities. Measurement Science Review, 10 (5), 166-175.Search in Google Scholar

[13] Arif, M., Ohtaki, Y., Nagatomi, R., Inooka, H. (2004). Estimation of the effect of cadence on gait stability in young and elderly people using approximate entropy technique. Measurement Science Review, 4 (2), 29-40.Search in Google Scholar

[14] Fu, L., He, Z.Y., Mai, R.K. (2008). Application of approximate entropy to fault signal analysis in electric power system. Proceedings of the CSEE, 28 (28), 68-73.Search in Google Scholar

[15] Pang, Q.L., Sun, T.J., Zhong, M.Y. (2007). Fault line detection based on rough set theory in indirectly grounding power system. Proceedings of the CSEE, 27 (4), 60-64.Search in Google Scholar

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