A Framework for Wide-area Monitoring of Tree-related High Impedance Faults in Medium-voltage Networks

  • Received : 2017.02.18
  • Accepted : 2017.07.18
  • Published : 2018.01.01


Wide-area monitoring of tree-related high impedance fault (THIF) efficiently contributes to increase reliability of large-scaled network, since the failure to early location of them may results in critical lines tripping and consequently large blackouts. In the first place, this wide-area monitoring of THIF requires managing the placement of sensors across large power grid network according to THIF detection objective. For this purpose, current paper presents a framework in which sensors are distributed according to a predetermined risk map. The proposed risk map determines the possibility of THIF occurrence on every branch in a power network, based on electrical conductivity of trees and their positions to power lines which extracted from spectral data. The obtained possibility value can be considered as a weight coefficient assigned to each branch in sensor placement problem. The next step after sensors deployment is to on-line monitor based on moving data window. In this on-line process, the received data window is evaluated for obtaining a correlation between low frequency and high frequency components of signal. If obtained correlation follows a specified pattern, received signal is considered as a THIF. Thereafter, if several faulted section candidates are found by deployed sensors, the most likely location is chosen from the list of candidates based on predetermined THIF risk map.

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Fig. 1. Power outages causes in the United States [4]

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Fig. 2. Current RMS of a THIF

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Fig. 3. Study area

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Fig. 4. Obtained white points representing trees’ crown inFig. 3

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Fig. 5. Location of sampling points

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Fig. 6. Electrical conductivity measurement of samples

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Fig. 7. EC values of 25 live poplar trees

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Fig. 8. Linear relationship between electrical conductivityand salt content of an electrolyte

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Fig. 9. False color composite (432) of study area

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Fig. 10. The reflectance data corresponding to each spectralband

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Fig. 11. The model fitted for electrical conductivity withthe R2 = 0.4409

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Fig. 12. Fundamental component and high frequencycomponents of tested trees

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Fig. 13. Distribution of intrinsic mode functions

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Fig. 14. Algorithm of Quantiles calculation

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Fig. 15. The quantile-quantile plots and estimated lines

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Fig. 16. HIF experiment under 20 kV power lines

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Fig. 17. Downloaded stored THIF current (mA)

Table. 1. Coefficients of regression equation

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Table 2. Max amplitude of THIF current (A)

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Table 3. Max amplitude of THIF current

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Table 4. The estimated maximum amplitude for high frequency components

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