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Assessment and Application Research on the Carrying Capacity of Township Power Supply Station Based on Big Data Analysis

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Intelligent Computing Theories and Application (ICIC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12463))

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Abstract

At present, the grid division of township power supply stations lacks guiding opinions, the grid division principle of each unit is not unified, and the assessment of the carrying capacity of each station has not formed a unified and reasonable assessment plan. As the power grid data resources of township power supply stations show typical big data characteristics, it is urgent to use big data analysis tools in the business analysis of township power supply stations. Based on this, this paper uses the clustering algorithm and subjective and objective weighting method to evaluate the scores and weights of each evaluation index from the dimensions of customer scale, line loss of the substation area and collaborative work order, and obtains the carrying capacity of each substation area and managers of each substation area, and studies the business application scenario of this model.

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References

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Author information

Authors and Affiliations

  1. State Grid Zhejiang Power Co., Ltd, Hangzhou, China

    Pan Weiwei, Shen Guang, Wu Yuebo & Huang Xiang

Authors
  1. Pan Weiwei
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  2. Shen Guang
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  3. Wu Yuebo
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  4. Huang Xiang
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Corresponding author

Correspondence to Pan Weiwei .

Editor information

Editors and Affiliations

  1. Institute of Machine Learning and Systems Biology, Tongji University, Shanghai, China

    De-Shuang Huang

  2. Electrical and Electronics Department, Polytechnic University of Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. School of Computer Science and Mathematics, Liverpool John Moores University, Liverpool, UK

    Abir Hussain

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Weiwei, P., Guang, S., Yuebo, W., Xiang, H. (2020). Assessment and Application Research on the Carrying Capacity of Township Power Supply Station Based on Big Data Analysis. In: Huang, DS., Bevilacqua, V., Hussain, A. (eds) Intelligent Computing Theories and Application. ICIC 2020. Lecture Notes in Computer Science(), vol 12463. Springer, Cham. https://doi.org/10.1007/978-3-030-60799-9_49

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  • DOI: https://doi.org/10.1007/978-3-030-60799-9_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60798-2

  • Online ISBN: 978-3-030-60799-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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