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

Abstract

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.

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

Fig. 2. Current RMS of a THIF

Fig. 3. Study area

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

Fig. 5. Location of sampling points

Fig. 6. Electrical conductivity measurement of samples

Fig. 7. EC values of 25 live poplar trees

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

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

Fig. 10. The reflectance data corresponding to each spectralband

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

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

Fig. 13. Distribution of intrinsic mode functions

Fig. 14. Algorithm of Quantiles calculation

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

Fig. 16. HIF experiment under 20 kV power lines

Fig. 17. Downloaded stored THIF current (mA)

Table. 1. Coefficients of regression equation

Table 2. Max amplitude of THIF current (A)

Table 3. Max amplitude of THIF current

Table 4. The estimated maximum amplitude for high frequency components