Investigation of frequency characteristics of typical PD and the propagation properties in GIS

Abstract

The secure operation of Gas Insulated Switchgear (GIS) is crucial for the bulk power systems, since the failure of GIS apparatus would cause severe interruption of power transforming and power supply at substations. Therefore, the monitoring and maintenance schemes of GIS devices have gradually taken the reliability-based indices into account, of which Partial Discharge (PD) levels in online monitoring are of substantial significance because PD serves as a major cause of insulation break-down. Ultra High Frequency (UHF) method is becoming widely adopted as the major inspection approach for PD in GIS. This paper presents the experiment-based results of the frequency characteristics of UHF signals caused by PD in typical defects using entire GIS operating system platforms. Specifically, the results covered the propagation attenuation of the UHF signals with peak to peak value and cumulative energy through typical structures, including basin-type insulators, Lshaped branch, isolating switches, current transformers, etc. The results serve as substantial criteria for optimal band width selection for high frequency detection, and as notable concerns to improve the sensitivity of UHF detection and the efficiency of online monitoring by effectively locating the external sensors for PD UHF detection.

Study of New Method Combined Ultra-High Frequency (UHF) Method and Ultrasonic Method on PD Detection for GIS

“…Electromagnetic wave is propagated in the form of transverse electromagnetic waves (TEM) transmission, and high-order transverse electric field wave (TE) and transverse magnetic field (TM) are established [3].UHF antenna is used to detect electromagnetic waves generated by the partial discharge of GIS for the analysis of electromagnetic wave [4].For ultrasonic method. are violently collided with each other and pressure is created in the moment of partial discharge in GIS.…”

Recurrent Neural Network for Partial Discharge Diagnosis in Gas-Insulated Switchgear

“…Time-resolved PD (TRPD) and phase-resolved PD (PRPD) analyses have been studied in order to examine the characteristics of PDs in GIS [18][19][20][21][22][23][24][25][26][27]. The TRPD-based method is a method of analyzing the time-domain features of PD pulses, frequency-domain features of PD pulses, and both time-domain and frequency-domain features of PD pulses [19][20][21]. The PRPD-based diagnostic method analyzes phase-amplitude-number (φ-q-n) measurements, where φ is the phase angle, q is the amplitude, and n is the number of discharges [26].…”

“…The PRPD-based diagnostic method analyzes phase-amplitude-number (φ-q-n) measurements, where φ is the phase angle, q is the amplitude, and n is the number of discharges [26]. It identifies the fault type by analyzing the number of PD pulses, the maximum amplitude, or the average amplitude in each phase [19][20][21]25,27,28]. From these features, fault types are classified by many methods, including a knowledge-based fuzzy logic analysis [26] and machine learning techniques such as K-means cluster analysis [23,29], artificial neural networks (ANNs) [19,27,30,31], or support vector machines (SVMs) [19][20][21]25,32,33].…”

Failure Prognosis of High Voltage Circuit Breakers with Temporal Latent Dirichlet Allocation

“…Degradation of the HVCB is caused by several types of stress and aging, such as mechanical maladjustment, switching arcs erosion, and insulation level decline. The existing literature covers a wide range of specific countermeasures, including mechanism dynamic features [8][9][10], dynamic contact resistance [11], partial discharge signal [12,13], decomposition gas [14], vibration [15], and spectroscopic monitoring [16]. Furthermore, numerous studies applied neural networks [8], support vector machine (SVM) [17], fuzzy logic [18], and other methods [19], to introduce more automation and intelligence into the signal analysis.…”