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Research on Pre-view Method of Safety Level of Cascading Trip for Power Grid

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Advanced Machine Learning Technologies and Applications (AMLTA 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1339))

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Abstract

This article introduces a method by which the power grid's security level can be observed in advance based on the expected initial failure. Firstly, based on the general form of cascading trip, this paper gives a mathematical expression of grid tripping based on cascading trip relay protection action behavior. According to the mathematical expression, the relationship between grid tripping and grid node injection power is discussed. According to this relationship, the distance between the node injection power under the current operation state and the nearest critical state node injection power is taken as the index to measure the power grid's security for cascading trip. According to this index, combined with various power grid constraints before and after the initial fault, a mathematical model for obtaining this safety index is given. This model is an optimized mathematical model. For the model, this paper gives a solution idea based on particle swarm. Finally, a few cases are performed in the IEEE-14 node system, and the calculations of the cases proved the accuracy of the proposed model and method.

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Acknowledgment

This research was financially supported by the Scientific Research Development Foundation of the Fujian University of Technology under the grant GY-Z17149, the Scientific and Technical Research Project of Fuzhou under the grant GY-Z18058 and Fuzhou Science and Technology Plan under the grant 2018-G-30.

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Authors and Affiliations

  1. School of Information Science and Engineering, Fujian University of Technology, No. 3 Xueyuan Road, University Town, Minhou, Fuzhou, 350118, Fujian, China

    Huiqiong Deng, Qinbin Li, Rongjin Zheng, Peiqiang Li & Kuo-Chi Chang

  2. Fujian Provincial University Engineering Research Center of Smart Grid Simulation Analysis and Integrated Control, Fuzhou, 350118, Fujian, China

    Huiqiong Deng, Qinbin Li, Rongjin Zheng & Peiqiang Li

  3. Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, No. 3 Xueyuan Road, University Town, Minhou, Fuzhou, 350118, Fujian, China

    Kuo-Chi Chang

  4. College of Mechanical & Electrical Engineering, National Taipei University of Technology, No. 1, Section 3, Zhongxiao East Road, Taipei, 10608, Taiwan

    Kuo-Chi Chang

  5. Department of Business Administration, North Borneo University College, Lot 47, Block-F, Alamesra Permai Plaza 2, Jln Sulaman, 88400, Kota Kinabalu, Sabah, Malaysia

    Huiqiong Deng, Qinbin Li, Rongjin Zheng, Peiqiang Li & Kuo-Chi Chang

Authors
  1. Huiqiong Deng
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  2. Qinbin Li
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  3. Rongjin Zheng
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  4. Peiqiang Li
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  5. Kuo-Chi Chang
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Corresponding author

Correspondence to Qinbin Li .

Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Computer and Information Faculty, Giza, Egypt

    Aboul-Ella Hassanien

  2. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Kuo-Chi Chang

  3. International Center for Informatics Research, Beijing Jaiotong University, Beijing, China

    Tang Mincong

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Deng, H., Li, Q., Zheng, R., Li, P., Chang, KC. (2021). Research on Pre-view Method of Safety Level of Cascading Trip for Power Grid. In: Hassanien, AE., Chang, KC., Mincong, T. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2021. Advances in Intelligent Systems and Computing, vol 1339. Springer, Cham. https://doi.org/10.1007/978-3-030-69717-4_79

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