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Non Time Domain Fault Detection Method for Distribution Network

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Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1303))

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Abstract

The traditional over-current relay protection method can not be directly applied to the active distribution network with renewable energy generation. In this paper, a non time domain fault detection method based on voltage signal amplitude spectrum and marginal spectrum is proposed. The fault is set in the distribution network. The voltage data obtained from monitoring points are processed and analyzed to obtain test samples to verify the reliability.

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Acknowledgements

This work was supported by 2019-HUZJTKJ-17.

Author information

Authors and Affiliations

  1. State Grid Huzhou Power Supply Company, Huzhou, China

    Jianwei Cao, Ming Tang, Ying Liu & Tao Huang

  2. China Ji Liang University, Hangzhou, China

    Zhihua Huang, Ying Wang & Yanfang Zhou

Authors
  1. Jianwei Cao
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  2. Ming Tang
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  3. Zhihua Huang
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  4. Ying Liu
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  5. Ying Wang
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  6. Tao Huang
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  7. Yanfang Zhou
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Corresponding author

Correspondence to Ying Wang .

Editor information

Editors and Affiliations

  1. School of Computer Science, University of Oklahoma, Norman, OK, USA

    Mohammed Atiquzzaman

  2. University of Aizu, Fukushima, Japan

    Neil Yen

  3. Shanghai University of Medicine and Health Sciences, Shanghai, China

    Zheng Xu

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Cite this paper

Cao, J. et al. (2021). Non Time Domain Fault Detection Method for Distribution Network. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2020. Advances in Intelligent Systems and Computing, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-4572-0_41

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  • DOI: https://doi.org/10.1007/978-981-33-4572-0_41

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-4573-7

  • Online ISBN: 978-981-33-4572-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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