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Hybrid Artificial Intelligence Technique Based Fault Location in a Long Transmission Line

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Recent Advances in Power Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 812))

Abstract

This paper recommends a fault distance estimation approach focusing on artificial intelligence (AI) based techniques in combination with signal processing techniques. Detailed analysis was carried out for the development of the procedure of the proposed approach. To minimize the computational burden of dealing with huge data set, a feature extraction process was applied to convert the data into a feature set. Thereafter to raise the precision and to make the training process fast, a feature selection technique was implemented where features with the utmost predictive power were selected from the whole set of features. The features of choice were then given to a support vector machine (SVM) or neural network (NN) for determining fault distance. The performance of the suggested technique in this paper was verified on the transmission line. To show the strength of discussed technique, a large number of operating conditions such as fault resistance, inception angle, type, and distance were taken. The obtained results specify the accuracy of the discussed scheme of fault location.

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Acknowledgements

This research work was funded by “Woosong University’s Academic Research Funding—2022”.

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Authors and Affiliations

  1. Department of Electrical Engineering, Veer Surendra Sai University of Technology (VSSUT), Burla, Odisha, India

    Papia Ray

  2. Department of Railroad and Electrical Engineering, Woosong University, Daejeon, South Korea

    Surender Reddy Salkuti

Authors
  1. Papia Ray
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  2. Surender Reddy Salkuti
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Corresponding author

Correspondence to Surender Reddy Salkuti .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, National Institute of Technology Jamshedpur, Jamshedpur, India

    Om Hari Gupta

  2. Faculty of Engineering and Applied Science, Ontario Tech University, Oshawa, ON, Canada

    Vijay Kumar Sood

  3. Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada

    Om P. Malik

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Ray, P., Salkuti, S.R. (2022). Hybrid Artificial Intelligence Technique Based Fault Location in a Long Transmission Line. In: Gupta, O.H., Sood, V.K., Malik, O.P. (eds) Recent Advances in Power Systems. Lecture Notes in Electrical Engineering, vol 812. Springer, Singapore. https://doi.org/10.1007/978-981-16-6970-5_36

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  • DOI: https://doi.org/10.1007/978-981-16-6970-5_36

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-6969-9

  • Online ISBN: 978-981-16-6970-5

  • eBook Packages: EnergyEnergy (R0)

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