Skip to main content
Log in

A Successive Geometric Segmentation Approach Applied to Double-Circuit Transmission Lines Fault Classification and Location

  • Published:
Journal of Control, Automation and Electrical Systems Aims and scope Submit manuscript

Abstract

This paper presents a new approach to address both fault classification and location in double-circuit power transmission lines. Fault diagnosis is achieved by using an algorithm based on the successive geometric segmentation approach. The proposed technique is able to generate both the topology and the weighting of neural networks. The input parameters are the magnitudes of phase voltages and currents measured in only one bus of a double-end fed transmission line. In order to validate the methodology, a comprehensive dataset of cross-country faults was simulated using a mathematical model. The results indicate high accuracy rate to fault diagnosis in double-circuit transmission lines compared to other ANN-based approaches found in the literature.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  • Bhalja, B. R., & Maheshwari, R. P. (2007). High-resistance faults on two terminal parallel transmission line: Analysis, simulation studies, and an adaptive distance relaying scheme. Power Delivery, IEEE Transactions on, 22(2), 801–812.

    Article  Google Scholar 

  • Cecati, C., & Razi, K. (2012). Fuzzy-logic-based high accurate fault classification of single and double-circuit power transmission lines. In Power electronics, electrical drives, automation and motion (SPEEDAM), 2012 international symposium on (pp 883–889).

  • Chen, C.-S., Liu, C.-W., & Jiang, J.-A. (2002). A new adaptive PMU based protection scheme for transposed/untransposed parallel transmission lines. Power Delivery, IEEE Transactions on, 17(2), 395–404.

    Article  Google Scholar 

  • De Dominicis, C. M., Ferrari, P., Flammini, A., Rinaldi, S., & Quarantelli, M. (2011). On the use of ieee 1588 in existing iec 61850-based sass: Current behavior and future challenges. Instrumentation and Measurement, IEEE Transactions on, 60(9), 3070–3081.

    Article  Google Scholar 

  • Dos Santos, R. C., & Senger, E. C. (2011). Transmission lines distance protection using artificial neural networks. International Journal of Electrical Power & Energy Systems, 33(3), 721–730.

    Article  Google Scholar 

  • Gaspar, W., Oliveira, E., Honorio, L., & Machado, L. (2014). Modified successive geometric segmentation method applied to power transformers faults diagnosis. Journal of Control, Automation and Electrical Systems, 25(3), 330–338.

    Article  Google Scholar 

  • Gonen, T. (2014). Electrical power transmission system engineer: Analysis and design (3rd ed.). Boca Raton, FL: CRC Press Taylor and Francis Group.

    Google Scholar 

  • Gottschalk, S. (2000). Collision queries using oriented bounding boxes. PhD thesis, The University of North Carolina, Chapel Hill, NC.

  • Gottschalk, S., Lin, M. C., & Manocha, D. (1996). Obbtree: A hierarchical structure for rapid interference detection. In Proceedings of the 23rd annual conference on computer graphics and interactive techniques, SIGGRAPH’96 (pp. 171–180). New York, NY: ACM.

  • Gracia, J., Mazon, A., & Zamora, I. (2005). Best ANN structures for fault location in single-and double-circuit transmission lines. Power Delivery, IEEE Transactions on, 20(4), 2389–2395.

    Article  Google Scholar 

  • Honório, L. M., Oliveira, E. J., Barbosa, D. A., Moraes, C. H., Almeida, R. M. A., & Boas, A. V. (2014). Construction of artificial neural networks for pattern recognition using a successive geometric segmentation method. Journal of Control, Automation and Electrical Systems. doi:10.1007/s40313-014-0126-6.

  • Jain, A., Thoke, A. S., Koley, E., & Patel, R. (2009). Fault classification and fault distance location of double circuit transmission lines for phase to phase faults using only one terminal data. In Power Systems, 2009. ICPS ’09. International Conference on (pp. 1–6).

  • Jamehbozorg, A., & Shahrtash, S. (2010). A decision tree-based method for fault classification in double-circuit transmission lines. Power Delivery, IEEE Transactions on, 25(4), 2184–2189.

    Article  Google Scholar 

  • Khorashadi-Zadeh, H. (2004). Artificial neural network approach to fault classification for double circuit transmission lines. In Transmission and distribution conference and exposition: Latin America, 2004 IEEE/PES (pp. 859–862).

  • Mazon, A., Zamora, I., Gracia, J., Sagastabeitia, K., Eguia, P., Jurado, F., et al. (2001). Fault location system on double circuit two-terminal transmission lines based on anns. In Power tech proceedings, 2001 IEEE Porto (Vol. 3, p. 5).

  • Oleskovicz, M., Coury, D., & Aggarwal, R. (2001). A complete scheme for fault detection, classification and location in transmission lines using neural networks. In Developments in power system protection, 2001, seventh international conference on (IEE) (pp. 335–338).

  • Osman, A., & Malik, O. (2004). Protection of parallel transmission lines using wavelet transform. Power Delivery, IEEE Transactions on, 19(1), 49–55.

    Article  Google Scholar 

  • Purohit, A. & Gohokar, V. (2015). Recent developments in distance protection of compensated transmission lines. In Pervasive computing (ICPC), 2015 international conference on (pp. 1–6).

  • Saravanan, N., & Rathinam, A. (2012). A comparative study on ann based fault location and classification technique for double circuit transmission line. In Computational intelligence and communication networks (CICN), 2012 fourth international conference on (pp. 824–830).

  • Schweitzer, E., & Hou, D. (1993). Filtering for protective relays. In WESCANEX 93. ’Communications, computers and power in the modern environment.’ Conference proceedings (pp. 15–23). IEEE.

  • Seyedi, H., Teimourzadeh, S., & Nezhad, P. (2014). Adaptive zero sequence compensation algorithm for double-circuit transmission line protection. Generation, Transmission Distribution, IET, 8(6), 1107–1116.

    Article  Google Scholar 

  • Silverman, B. W. (1998). Density estimation for statistics and data analysis. London: Chapman and Hall.

    MATH  Google Scholar 

  • Wang, M.-H. (2003). A novel extension method for transformer fault diagnosis. Power Delivery, IEEE Transactions on, 18(1), 164–169.

    Article  Google Scholar 

  • Warlyani, P., Jain, A., Thoke, A. S., & Patel, R. N. (2011). Fault classification and faulty section identification in teed transmission circuits using ANN. International Journal of Computer and Electrical Engineering, 3(6), 807–811.

    Article  Google Scholar 

  • Wei-Qi, J., Qian-Jin, L., & Chuan-Jian, L. (2011). Review of fault location for double-circuit parallel transmission lines on the same pole. In Advanced power system automation and protection (APAP), 2011 international conference on (Vol. 2, pp. 1125–1129).

  • Zin, A., & Abdul Karim, S. (2007). The utilization of digital fault recorders in protection system analysis on Tenaga Nasional Berhad transmission system. Power Delivery, IEEE Transactions on, 22(4), 2040–2046.

    Article  Google Scholar 

Download references

Acknowledgments

The authors acknowledge the agreement CAPES-FCT, PNPD, PRODOC, FAPEMIG, and INERGE (National Institute of Energy) for the given support.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wander Antunes Gaspar Valente.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gaspar Valente, W.A., de Mello Honório, L., de Oliveira, E.J. et al. A Successive Geometric Segmentation Approach Applied to Double-Circuit Transmission Lines Fault Classification and Location. J Control Autom Electr Syst 27, 452–462 (2016). https://doi.org/10.1007/s40313-016-0252-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40313-016-0252-4

Keywords

Navigation