Partial discharge (PD) detection is a widely extended technique for electrical insulation diagnosis. Ultrahigh-frequency detection techniques appear as a feasible alternative to traditional methods owing to their inherent advantages such as the capability to detect PDs online and to locate the piece of equipment with insulation problems in substations and cables. In this paper, four antennas are thoroughly studied by means of their theoretical and experimental behavior when measuring electromagnetic pulses radiated by PD activity. The theoretic study of the band of frequencies in which the pulse emits and the measurement of the parameters $S_{11}$ are complemented with the frequency response and wavelet transform of a set of 500 time signals acquired by the antennas, and the results are analyzed in detail.

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Antenna Parametrization for the Detection of Partial Discharges

Partial-discharging (PD) test is one of the most effective methods for insulation diagnosis. Because of the advantages of ultra-high frequency (UHF) electromagnetic wave, UHF signals radiated by PD have been widely used to locate faults on power equipment. Time delay estimation is not only on the basis of the PD localization algorithm, but is also the key in determining the localization accuracy. Currently, common methods are the threshold value method, energy accumulation method, and the cross-correlation analysis method, etc. However, field signals always include a variety of unknown noises, so common methods cannot be effective enough. This paper proposes time delay estimation algorithms based on four-order cumulant and bispectrum, and gives their computational realization. These algorithms have a prominent advantage of being insensitive to Gaussian noises with unknown correlation properties. The time delay of simulated UHF signals with Gaussian noises and fixed-frequency interference is estimated by the given algorithms. Numerical robustness of the algorithms is verified. Finally, time delays of field UHF signals received by UHF antennas are estimated, and then substituting the sequence of time delay estimations into the localization equations based on the time difference and 3-D coordinate of the PD source can be calculated accurately. The effectiveness and practicability of this algorithm are verified.

Robust Time Delay Estimation Method for Locating UHF Signals of Partial Discharge in Substation

Partial discharge (PD) is the manifestation of insulation degradation, and it is regarded as a great risk in the field of industrial high-voltage insulation system. In this paper, the direction-of-arrival (DOA) estimation algorithm is used for the localization of partial-discharge source. The intersecting point of two rays, which come from two different directions measured by two uniform linear arrays (ULAs), can be regarded as the plane location of partial-discharge source. Fast rise times of partial-discharge pulses result in a wide electromagnetic spectrum, thus this paper focuses on the DOA estimation of wideband signals. The technique of multimodal joint sparse representation (MJSR) has been used to improve the performance of biometrics recognition. Here, we extend it to DOA estimation. The received data are represented by a sparse linear combination of potential steering vectors, while constraining the observations from different frequencies subject to sharing the same sparsity pattern. Based on the simultaneous orthogonal matching pursuit (SOMP) and alternating direction method of multipliers (ADMM), a hard threshold algorithm is proposed for DOA estimation. In order to reduce the computational complexity of hard threshold algorithm, an improved soft threshold DOA estimation algorithm based on the ADMM is proposed as well. The effectiveness of the proposed algorithms is validated by simulations and real tests.

PD Source Diagnosis and Localization in Industrial High-Voltage Insulation System via Multimodal Joint Sparse Representation

Partial discharge (PD) is the main sign of the insulation deterioration; therefore, the online PD localization of the power transformers can provide the equipment degradation characteristics and has great value for the power grid. Because of some unique merits, acoustic PD detection is one of the best options for such applications. However, when discharges happen inside the windings, precise PD localization by acoustic method becomes very challenging. As the acoustic PD signal can be reverberated and distorted along its propagation, the type and number of sensors, with their installation, should be carefully studied and selected. In this paper, the acoustic wave propagation inside the transformer is explored via numerical simulation. Based on the understanding of wave propagation, a novel-structure fiber-optic acoustic sensor array is properly designed and installed into one phase winding, which is from a real 35 kV transformer. Experimental verification shows that, by using this proposed design, PD localization with less than 5-cm error can be achieved. Therefore, the novel sensor array developed in this paper, together with the installation and localization method, unveils a novel access to accurate online PD localization, especially for those PDs which happen inside transformer windings.

Partial Discharge Localization Inside Transformer Windings via Fiber-Optic Acoustic Sensor Array

Real-time data of high-voltage infrastructures collected by wireless sensors are the foundation of many smart grid applications. Energy harvesting can be an effective solution for autonomous, self-powered wireless sensors. In this paper, a coil with a novel helical core is proposed and optimized to scavenge the magnetic field energy efficiently near equipment carrying large currents. Due to the special design of the helical core, the path of the magnetic flux inside the core can be significantly increased, which leads to a reduction of the demagnetizing field. Therefore, the proposed core can generate a much higher flux density (hence more power) compared with conventional designs. The selection of the core material is studied and it is found that high permeability ferrite is the most suitable material. Experimental results show that the proposed helical coil with only 400 turns of wire can have a power density of ${\rm{2.1\,\mathrm{\mu} W/ cm}}^{3}$ when placed in a magnetic flux density of $7\,\mathrm{\mu} T_{{\rm{rms}}}$ . This value is bigger than any of the existing designs if placed in the same magnetic field. If more wires can be wound on the core, an even higher power density could be obtained. Therefore, the proposed design is a very efficient method for scavenging the magnetic field energy for a wide range of smart grid applications.

A High-Efficiency Helical Core for Magnetic Field Energy Harvesting

Partial discharges (PDs) generate wideband radio-frequency interference which can be used for noninvasive monitoring of discharges. This paper presents a novel method based on this principle for PD monitoring of substations. The significant advantage of this method lies in the ability to detect PD sources in energized equipment anywhere within a substation compound during normal operating conditions. The results obtained from the prototypes installed in the U.K. and U.S. substations are reported. Results include correlation with apparent charge and daily recordings obtained before, during, and after the failure of a 132-kV current transformer and 69-kV voltage transformer.

RF-Based Partial Discharge Early Warning System for Air-Insulated Substations

Environmentally friendly gases have been widely investigated to replace sulphur hexafluoride (SF6) in compressed gas insulated equipment for the power industry. This work presents the experimental investigations on the gas stability of HFO1234ze(E) (hereinafter referred to as C 3 H 2 F 4 ) where a unique first breakdown voltage behavior is found for AC, DC and lightning impulse (LI) voltages. A splatter of dark colored soot is observed on the plane electrode after the first breakdown that is followed by consecutive LI breakdowns chopped on the front. The breakdown characteristic stabilizes after the first voltage withstand and the 50% breakdown voltage (U 50 ) is calculated using the subsequent stabilized data series. This first breakdown behavior of C 3 H 2 F 4 is consistently observed for different tested electrode materials and configurations. The voltage difference between the first breakdown and U 50 varies significantly due to the work function of the electrode material and electric field uniformity. For AC breakdowns with comparatively higher discharge energy, the data series is more consistent after the first breakdown but with significant level of soot formation indicating that this is the main influencing factor for the first breakdown effect. Soot is identified as fluorinated carbon through X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) analyses.

L. van der Zel

Papers

RF-Based Partial Discharge Early Warning System for Air-Insulated Substations

Anomalous First Breakdown Behavior for HFO1234ze(E)