Abstract
This paper elaborated a new relaying scheme for fault detection and classification of shunt faults comprising of multi-location faults and evolving faults which are more severe in double-circuit transmission line. In these work, two DWT-ANN modules have been proposed to detect and classify multi-location faults and evolving faults using voltage and current signals of either end of a double-circuit transmission line. A 400 kV transmission system of Chhattisgarh state has been modeled in RSCAD software environment of real-time digital simulator (RTDS) to replicate various real-time fault scenarios and further analysis has been done in MATLAB software. The results demonstrated that all shunt faults are properly detected/classified in less than 10 ms. The distinctiveness of the DWT-ANN module is that it accurately detects/discriminates using one-terminal measurements/data only and it avoids maloperation of three-phase transmission line of another healthy circuit also, which has not been reported yet simultaneously.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Swetapadma, A., Yadav, A.: Improved fault location algorithm for multi-location faults, transforming faults and shunt faults in thyristor controlled series capacitor compensated transmission line. IET Gener. Transm. Distrib. 9(13), 1597–1607 (2015)
Swetapadma, A., Yadav, A.: All shunt fault location including cross-country and evolving faults in transmission lines without fault type classification. Electr. Power Syst. Res. 123, 1–12 (2015)
Yadav, A., Dash, Y.: An overview of transmission line protection by artificial neural network: fault detection, fault classification, fault location, and fault direction discrimination. Adv. Artif. Neural Syst. Article ID 230382, 1–20 (2014)
Dalstein, T., Kulicke, B.: Neural network approach to fault classification for high speed protective relaying. IEEE Trans. Power Deliv. 10, 1002–1011 (1995)
Agarwal, R.K., Xuan, Q.Y., Dunn, R.W., Johns, A.T., Bennett, A.: A novel fault classification technique of double-circuit lines based on a combined unsupervised/supervised neural network. IEEE Trans. Power Deliv. 14, 1250–1256 (1999)
Silva, K.M., Souza, B.A., Brito, N.S.D.: Fault detection and classification in transmission lines based on wavelet transform and ANN. IEEE Trans. Power Deliv. 21, 2058–2063 (2006)
Mahanty, R.N., Dutta Gupta, P.B.: Comparison of fault classification methods based on wavelet analysis and ANN. J. Electr. Power Compon. Syst. 34, 47–60 (2006)
Yadav, A.: Comparison of single and modular ANN based fault detector and classifier for double-circuit transmission lines. Int. J. Eng. Sci. Technol. 4, 122–136 (2012)
Skok, S., Marusic, A., Tesnjak, S., Pevik, L.: Double-circuit line adaptive protection based on kohonen neural network considering different operation and switching modes. Larg. Eng. Syst. Conf. Power Eng. 2, 153–157 (2002)
Jain, A., Thoke, A.S., Patel, R.N., Koley, E.: Inter-circuit and cross-country fault detection and classification using artificial neural network, INDICON. In: 2010 Annual IEEE, pp. 1156–1161 (2010)
Acknowledgements
The authors acknowledge the financial support of Central Power Research Institute, Bangalore, for funding the project no. RSOP/2016/TR/1/22032016, dated: 19.07.2016. The authors are thankful to the Head of the institution as well as Head of the Department of Electrical Engineering, National Institute of Technology, Raipur, for providing the research facilities to carry this research project. The authors are grateful to the local power utility (Chhattisgarh State Power Transmission Company Limited) for their cooperation in providing valuable data to execute this research work.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Ashok, V., Yadav, A., Vinod Kumar Naik (2019). Fault Detection and Classification of Multi-location and Evolving Faults in Double-Circuit Transmission Line Using ANN. In: Nayak, J., Abraham, A., Krishna, B., Chandra Sekhar, G., Das, A. (eds) Soft Computing in Data Analytics . Advances in Intelligent Systems and Computing, vol 758. Springer, Singapore. https://doi.org/10.1007/978-981-13-0514-6_31
Download citation
DOI: https://doi.org/10.1007/978-981-13-0514-6_31
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-0513-9
Online ISBN: 978-981-13-0514-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)