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Parameter-Free Fault Location Algorithm for Distribution Network T-Type Transmission Lines

Author

Listed:
  • Chengbin Wang

    (Key Laboratory of Power System Intelligent Dispatch and Control (Shandong University), Ministry of Education, Jinan 250061, China)

  • Zhihao Yun

    (Key Laboratory of Power System Intelligent Dispatch and Control (Shandong University), Ministry of Education, Jinan 250061, China)

Abstract

T-type transmission lines have been increasingly used in distribution networks because of the distributed generation integration, but inaccurate line parameters will cause significant error in the results of most existing fault location algorithms for this kind of line. In order to improve the precision, this paper proposes a new fault location algorithm taking line parameters as unknowns. The fault is assumed to occur on each section, and corresponding ranging equations can be built based on one set of three-terminal post-fault synchronous measurements, without using line parameters as inputs. Then, more sets of measurements are utilized to increase the redundancy of equations to resist the influence of data error. The reliable trust-region algorithm is used to solve each group of equations, but only equations of the assumed faulty section with the actual fault point can give the reasonable solutions, accordingly identifying the fault point. The performance of the proposed method is thoroughly investigated with MATLAB/Simulink. The results indicate that the algorithm has a high accuracy and is basically unaffected by fault position, fault resistance, unbalanced fault type, line parameter, and data error.

Suggested Citation

  • Chengbin Wang & Zhihao Yun, 2019. "Parameter-Free Fault Location Algorithm for Distribution Network T-Type Transmission Lines," Energies, MDPI, vol. 12(8), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1534-:d:225275
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    Citations

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    Cited by:

    1. Susana Martín Arroyo & Miguel García-Gracia & Antonio Montañés, 2019. "The Half-Sine Method: A New Accurate Location Method Based on Wavelet Transform for Transmission-Line Protection from Single-Ended Measurements," Energies, MDPI, vol. 12(17), pages 1-15, August.
    2. Simone A. Rocha & Thiago G. Mattos & Rodrigo T. N. Cardoso & Eduardo G. Silveira, 2022. "Applying Artificial Neural Networks and Nonlinear Optimization Techniques to Fault Location in Transmission Lines—Statistical Analysis," Energies, MDPI, vol. 15(11), pages 1-24, June.

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