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A Fault-Tolerant Location Approach for Transient Voltage Disturbance Source Based on Information Fusion

Author

Listed:
  • Guoqing Weng

    (College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China)

  • Feiteng Huang

    (College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China)

  • Jun Yan

    (Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881, USA)

  • Xiaodong Yang

    (College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China)

  • Youbing Zhang

    (College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China)

  • Haibo He

    (Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881, USA)

Abstract

This paper proposed a fault-tolerant approach based on information fusion (IF) to automatically locate the transient voltage disturbance source (TVDS) in smart distribution grids. We first defined three credibility factors that will influence the reliability of the direction-judgments at each power quality monitor (PQM). Then we proposed two rules of influence and a verification factor for the distributed generation (DG) integration. Based on the two sets of direction-judgment criteria, a novel decision-making method with fault tolerance based on the IF theory is proposed for automatic location of the TVDS. Three critical schemes, including credibility fusion, conflict weakening, and correction for DG integration, have been integrated in the proposed fusion method, followed by a reliability evaluation of the location results. The proposed approach was validated on the IEEE 13-node test feeder, and the TVDS location results demonstrated the effectiveness and fault tolerance of the IF based approach.

Suggested Citation

  • Guoqing Weng & Feiteng Huang & Jun Yan & Xiaodong Yang & Youbing Zhang & Haibo He, 2016. "A Fault-Tolerant Location Approach for Transient Voltage Disturbance Source Based on Information Fusion," Energies, MDPI, vol. 9(12), pages 1-23, December.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:12:p:1092-:d:85672
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    References listed on IDEAS

    as
    1. Nantian Huang & Shuxin Zhang & Guowei Cai & Dianguo Xu, 2015. "Power Quality Disturbances Recognition Based on a Multiresolution Generalized S-Transform and a PSO-Improved Decision Tree," Energies, MDPI, vol. 8(1), pages 1-24, January.
    2. Meng-Hui Wang & Her-Terng Yau, 2014. "New Power Quality Analysis Method Based on Chaos Synchronization and Extension Neural Network," Energies, MDPI, vol. 7(10), pages 1-18, October.
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