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Reference: ISH2015_23

Type:
ISH Collection
Title:

Comparison of Power Arcing Faults Electromagnetic Source Detection and Location Methods

 

Abstracts

Using strategically placed antennas the electric arc electromagnetic (EM) radiation can be detected at remote distance and, at some extent, the arc source location can also be determined. For decades many works have proposed detection methods, but none has been practiced for arcing fault location in power systems. It is because this type of fault is not well understood and the protection against arcing faults has not been developed. A few radiation-based works in power systems have been devoted to partial discharges and lightning detection, and they concern mainly establishing the presence of EM radiation signals without presenting effective means to pinpoint these arc sources. This paper investigates feasibility of detecting and locating the actual source point in 3D Cartesian plane through the multiple radiation detection and location methods. In this study the following six different arcing fault detection and location methods are compared in pinpointing electric arc electromagnetic (EM) sources in power systems: cross-correlation method (XCORR), first peak of arrival method (FPA), leading edge of first arrival peak method (LEFAP), energy attenuation method (ENERGY) or inverse square method, angle of arrival method (AoA), and wavelet analysis (WAVELET). It is evident that the interpretation of the results based on these six methods depends to some extent on statistical methods; therefore, the methods undergo statistical analysis evaluation in order to determine a suitable power arc location algorithm which can be used in real field measurements. Specifically, analysis of variance (ANOVA) and multiple linear regressions (MLR) are applied for statistical estimation and for comparison of the result with the actual source point. The results show that it is feasible for the six methods, using the radiated signals from arcing fault, to detect and locate the arcing source with a mean square error less than 10%. The cross-correlation among these proposed methods shows a better potential in clarifying the electric arc source position when compared with other algorithms.
 

File Size: 669,5 KB

Year: 2015

 
 
 
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