We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Local Outlier Factor based Data Mining Model for Three Phase Transmission Lines Faults Identification

by Tan Yong Sing, Emran Bin Siraj Syahrel, Pratap Nair Marimuthu, Raman Raguraman, K. Nithiyananthan
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 130 - Number 2
Year of Publication: 2015
Authors: Tan Yong Sing, Emran Bin Siraj Syahrel, Pratap Nair Marimuthu, Raman Raguraman, K. Nithiyananthan
10.5120/ijca2015906878

Tan Yong Sing, Emran Bin Siraj Syahrel, Pratap Nair Marimuthu, Raman Raguraman, K. Nithiyananthan . Local Outlier Factor based Data Mining Model for Three Phase Transmission Lines Faults Identification. International Journal of Computer Applications. 130, 2 ( November 2015), 17-23. DOI=10.5120/ijca2015906878

@article{ 10.5120/ijca2015906878,
author = { Tan Yong Sing, Emran Bin Siraj Syahrel, Pratap Nair Marimuthu, Raman Raguraman, K. Nithiyananthan },
title = { Local Outlier Factor based Data Mining Model for Three Phase Transmission Lines Faults Identification },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 130 },
number = { 2 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 17-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume130/number2/23181-2015906878/ },
doi = { 10.5120/ijca2015906878 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:23:57.189350+05:30
%A Tan Yong Sing
%A Emran Bin Siraj Syahrel
%A Pratap Nair Marimuthu
%A Raman Raguraman
%A K. Nithiyananthan
%T Local Outlier Factor based Data Mining Model for Three Phase Transmission Lines Faults Identification
%J International Journal of Computer Applications
%@ 0975-8887
%V 130
%N 2
%P 17-23
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The main objective of this paper is to design and developed a model of power system transmission lines fault identification using Local Outlier Factor (LOF) technique based on data mining. 9 bus power system and 30 bus power systems overhead transmission line fault of are simulated as a test cases using PowerWorld software and the LOF computations using Matlab software. The proposed model consists of two main steps; the first step is used to determine single line-to-ground (SLG) fault and 3 phase fault. The second step was used to determine line-to-line (LL) fault and double line-to-ground (DLG) fault. The second step is required uninterrupted phase voltage in order to distinguish between LL fault and DLG faults. The proposed model successfully identified asymmetrical faults and symmetrical faults that particular single bus fault.

References
  1. T.Takagi, Y. Yamakoshi, R. Kondow, M. Yamaura, T. Matsushima, “Development of a New Type Fault Locator Using the One-Terminal Voltage and Current Data.” IEEE Power EngRev. PER-2(8), 59-60 (1982).
  2. J.Rohrig, “Location of Faulty Places by Measuring with Cathode Ray Oscilloscope”.ElecticitatZeitschrift, 19th Feb, 1931, pp 241-242.
  3. Amir Tabatabaei, Mohammad-Reza Mosavi, AbdolrezaRahmati, “Fault Location Techniques in Power System based on Traveling Wave using Wavelet Analysis and GPS Timing”, Electrical Review, ISSN 0033-2097, 2012.
  4. Kulicke B, Dalstein T. “Neural Network Approach To Fault Classification For High Speed Protective Relaying”, IEEE Transactions on Power Delivery, vol. 4, 1995, pp. 1002-1009.
  5. Aravinda Surya. V, EbhaKoley, Anamika Yadav and A.S.Thoke, “Artificial Neural Network Based Fault Locator for Single Line to Ground Fault in Double Circuit Transmission Line”, DOI: 10.7763/IPEDR, vol. 75, 2014
  6. S.Sangiovanni, A.Ferrero, E. Zapitelli, “A Fuzzy Set Approach To Fault Type Identification In Digital Relaying”, IEEE Trans. Power Delivery, vol.10, pp. 169-175, January 1995.
  7. W.W.L. Keerthipala and H.Wang, “Fuzzy Neuro Approach To Fault Classification For Transmission Line Protection”, IEEE Trans. Power Delivery, vol.13, pp.1093-1104, October 1998.
  8. J.Vital Reddy and B.Das, “Fuzzy-Logic Based Fault Classification Scheme For Digital Distance Protection”, IEEE Trans. Power Delivery, vol.20, pp. 609-616, April 2005.
  9. Yagang Zhang, Jing Ma, Jinfang Zhang, Zenping Wang, “Application of Data Mining Theory in Electrical Engineering”, SciRes,DOI:10.4236/eng.2009.13025.
  10. M. Breuning, H-P.Kriegel, R. Ng, and J. Sander. “LOF: Identifying Density-Based Local Outliers”. In Proc. of 2000 ACM SIGMOD International Conference on Management of Data (SIGMOD’00), Dallas, Texas, pp 93-104, 2000.
  11. J.M. Aldaz, S.Barza, M.Fuji and M.S. Moslehian. “Advances in Operator Cauchy-Schwarz Inequalities and Their Reverse, Ann. Func.Anal. 6 (2015), no.3, p275-295.
Index Terms

Computer Science
Information Sciences

Keywords

Power system asymmetrical faults symmetrical fault Transmission lines

Powered by PhDFocusTM