Development of PRPS Conversion Algorithm and Generator Using PRPD Pattern of Underground Power Transmission Cable

The task of detecting and classifying Partial Discharge (PD) in switchgear remains challenging due to the presence of inherent noise and the subtle differences among various PD signals under different operational conditions. Traditional PD detection methods have primarily relied either on analyzing time-series waveforms or on employing Phase-Resolved Partial Discharge (PRPD) patterns, which utilize extensive statistical information for classification. However, these approaches are notably susceptible to variations in hardware configurations and signal-to-noise ratios (SNR), limiting their effectiveness in real-world applications. This paper proposes a novel approach that enhances PD detection through multimodal fusion of time-series signals and PRPD patterns. Our method innovatively integrates these modalities by leveraging the statistical features from PRPD to enrich the time-series data, thereby extracting features that are both hardware-robust and domain-invariant. This dual-modal fusion provides a deeper insight into the characteristics of PD, enabling better discrimination among different types of discharges. Furthermore, our strategy emphasizes the learning of domain-invariant features, ensuring the model’s flexibility across different hardware setups and environmental conditions. We conducted comprehensive experiments with data collected from multiple sensors under varied conditions, demonstrating the superiority of our method compared to existing methods. The results reveal a significant improvement in PD detection accuracy and robustness, highlighting the practical utility of our method in complex and varied field environments.

This paper proposes a practical partial discharge (PD) severity analysis based on three factors as repetition rate, amplitude and gap time between positive and negative pattern on a phase resolved partial discharge (PRPD) pattern. The PDs are measured by using conventional and unconventional method. The PD amplitude represents PD size. Repetition rate is an average number of PD pulses per second. Gap time is a time distance between two clusters on positive and negative sides in PRPD pattern. Seven 6.6 kV motors were investigated by analysing three parameters, the results show that seven motors encountered high, moderate and low PD severity according to amplitude, repetition rate and gap time. In the first motor, the PRPD pattern shows slot discharge with a high repetition rate and a narrow gap time. This indicates the high risk to motor failure within a short period. The slot discharge was found at stator conductor through ground wall insulation to stator core. In the second motor, the PRPD pattern shows the slot discharge with high repetition rate with the gap time about 5.88 ms. Subsequently, a conventional method according to IEC60270 was performed. The problem was confirmed by visual inspection as stator slot damage by loosen wedge. Finally, the repetition rate, amplitude and gap time analysis were performed with another 5 motors. The results show the different PD severity that were further investigated and confirmed by visual inspection. This PD severity analysis could help to easily analyse, identify problem, predict PD severity and possibility of failure.

This paper presents an investigation on the off-line Partial Discharge (PD) and localization for 1 unit of in-service 5 MVA 33/6.9 kV oil immersed transformer. First, Dissolved Gas Analysis (DGA) was performed to confirm the existence of PD activities. Next, offline PD measurements were carried out on both LV and HV windings. Once the transformer has been energized, PD localization was performed at different sections of the transformer tank. It is found that HV windings are having possible multiples PD activities based on offline Phase-Resolved Partial Discharge (PRPD) pattern and PD localization.

This paper proposes a polar coordinate pattern approach to characterize the floating electrode defect in gas‐insulated metal‐enclosed switchgear (GIS). A 220‐kV GIS bus bar cavity is taken as an object to design the physical model of the floating electrode defect. The partial discharge (PD) development process is studied when the applied voltage is gradually increasing. The phase‐resolved partial discharge (PRPD) patterns and the polar coordinate patterns at different voltage levels are accessed through phase‐resolved pulse sequence (PRPS) data in the ultrahigh‐frequency (UHF) measurement. The proposed polar coordinate pattern approach does not use the traditional positive half‐cycle and negative half‐cycle analysis method in the PRPD pattern. It uses the clustering results to analyze the characteristics of the PD. It can be concluded that there are several advantages to the polar coordinate pattern. First, in the polar coordinate pattern, the phase is in a head‐to‐tail arrangement, so the observation of the PD phase characteristics can be more intuitive. Second, the polar coordinate pattern makes the calculated phase median, amplitude median, and centroid meaningful. With the voltage increasing, the variation law of the phase median and centroid can be observed. Third, the discharge parameters, which are based on the quadrant and statistical theory and the cosine similarity proposed in this paper, are from a new point of view. They can make a clear description of the characteristics of the floating electrode defect quantitatively, which can be distinguished from other insulation faults. Additionally, the continuous mode and phase mode at different voltage levels measured by acoustic detection are obtained to further demonstrate the PD development process. The acoustic results agree with the UHF measurement results. The efficiency and rationale of the polar coordinate pattern are further verified. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

This study is focused on solution to the problem that may occur due to noise signals when using the image obtained through the conventional partial discharge preprocessing methods as inputs to the CNN-based partial discharge pattern classifier. To solve such problem, a new data preprocessing method is proposed by considering a projection technique. In the data information obtained through the conventional partial discharge preprocessing methods, data information of useless noise signal leads to the problem of performance degradation when constructing highly qualified pattern classifier based on the data information of partial discharge signal. The proposed preprocessing method called as ‘Projection’ in this study is designed to solve this problem and improve a classification performance of CNN-based partial discharge pattern classifier. First of all, through GIS simulation, one-dimensional partial discharge data is obtained as five cases such as corona discharge, floating discharge, insulator discharge, free particle discharge, and steady state (noise) in an environment with a noise signal by using a UHF sensor. After that, by applying the two conventional partial discharge preprocessing methods such as PRPS(Phase Resolved Pulse Sequence), PRPD(Phase Resolved Partial Discharge) and the proposed partial discharge preprocessing method, one-dimensional partial discharge data is transformed into 3 data types such as image set of PRPS, image set of PRPD, and image set of Projection. Finally each image set is used as inputs to the designed CNN-based partial discharge pattern classifier. Through the comparative analysis of the feature maps of each layer in CNN as well as the performance accuracy of partial discharge pattern classification for each image set, the superiority of the proposed preprocessing method is demonstrated.

The reliability of electrical assets is greatly influenced by the quality of their insulations. Key power installations such as power cables are manufactured with polymer-based materials as part of their insulation system. However, accelerated ageing of equipment insulations due to manifestation of defect(s), and partial discharges (PDs) can offset the operation of these systems or even lead to breakdowns. In this study, a non-deterministic model to simulate the phenomenon of repetitive discharges in a spherical air-filled cavity within a practical power cable has been investigated. In addition, the work contributes to the understanding of PD behaviour and field distribution under different ageing conditions considering changes in cavity surface conductivity. First, a section of the practical XLPE cable containing the cavity is developed in 2D using COMSOL software, and a finite element analysis (FEA) of the electric field distribution within the cable insulation is performed. The magnitude of the cavity local field, that is enough to ignite a PD, is investigated. Alongside the COMSOL model, the activity of sustained internal PD is simulated in MATLAB by introducing a random sample generating factor and adjusting the model’s parameters to obtain something close to the practical results. Furthermore, the impact of continuous PD in the power cable under different cavity dimensions and surface conductivity is likewise investigated, and a phase resolved PD (PRPD) pattern is established. The result shows that the magnitude and number of PDs per cycle increase as the cavity size and its surface conductivity increase. Finally, when the cavity surface conductivity rises, the amplitude of the electric field generated by the surface charge distribution and the number of PDs per cycle approach their maximum values.

Partial discharge detection on power equipment using a magneto-resistive sensor

The paper describes the research on partial discharges (PD) characteristics in various types of power transmission lines insulation defects. Thirteen types of insulation defects were considered. PD measurements were performed using the AC high voltage source and commercial PD registration device. Phase-resolved partial discharge (PRPD) patterns, average apparent charge, and PD intensity were obtained for each defect type. The research results showed that most overhead lines insulators defects had relatively high PD intensity with small average apparent charge. Several insulators’ defects showed a low average charge and intensity, but insulators’ bodies in these cases were cut and could be destructed by mechanical loads. Power cable samples showed relatively high intensity and average charge in case of the cable termination defect. However, the needle grounding electrode defect showed considerable average charge and intensity. The obtained results will be useful for the defect type recognition tools development and PRPD patterns base extension.

Partial discharges (PD) may take place in solid and liquid insulating materials. This paper reports experimental results on partial discharges in low density polyethylene (LDPE) and transformer oil in divergent field under AC voltage. The applied voltage was adjusted from low voltage up to the partial discharge inception and was increased to higher voltage to get PD patterns. The measurement of the partial discharges was conducted using a PD measurement system which able to measure PD magnitude as well as phase of PD occurrence. The partial discharge pulses were recorded and presented in phase resolved patterns. The measurement results showed that the applied voltage significantly influenced the magnitude as well as the phase of PD occurrence. The PD patterns from solid material were different with those from liquid insulating materials. The characteristics of the PD in both materials were analyzed and modeled. In order to know better the characteristics of the PD, phase resolved simulation of PD were conducted and the role of applied voltage was investigated. The validity of the simulation was assessed based on the phase resolved PD distribution. It is shown that PD patterns from simulation are in good agreement with experimental results.

Partial discharge (PD) characteristics of hexadecane were studied in a needle-plane electrode geometry under AC field with a 20 μm tip radius tungsten needle. PD experiments were conducted on samples containing known concentrations of aromatic and corrosive sulfur compounds. Partial discharge inception voltage (PDIV), streamer repetition rates, and phase resolved PD (PRPD) patterns were acquired. Ionization potentials (IP) and electron affinities (EA) of hexadecane and the additives were calculated with density functional theory (DFT) and correlated with the PD characteristics. Low IP and negative EA of the additives relative to hexadecane increased the number of positive and negative streamers initiated, except for additives that contained an electron donating group on the aromatic ring. Low IP and positive EA for polyaromatic hydrocarbons (PAH) and corrosive sulfur compounds decreased the number of negative streamers initiated due to large electron capture cross sections. Copper sulfide particulates caused the greatest changes in PD characteristics as a result of its semi-conductive nature.

Investigation of partial discharge characteristics in XLPE cable insulation under increasing electrical stress

Dry-type transformers require little maintenance and are more environmentally friendly with respect to traditional oil-and-paper design. However, partial discharges (PDs) and thermal stress may lead to aging and—eventually—failure of the insulation. Diagnostics of their conditions—often performed by means of PD measurement—can be tricky, as PD activity depends on many parameters. In this work, a cast-resin power transformer is aged by means of 28 heating/cooling thermal cycles, to reproduce the thermal–electrical stress it may experience in operation. PD activity is monitored during the cooling branch of each cycle using a high-frequency current transformer (HFCT) to measure the current bled to the ground by the transformer shield, whose results are compared to the apparent charge measured by an IEC 60270-compliant commercial system installed on the medium-voltage (MV) winding. The effect of temperature and aging (number of cycles) is then investigated. The results show good agreement between the two measuring systems, in terms of both the phase-resolved partial discharge (PRPD) patterns and the average intensity trend over time. According to the intensity dependence on temperature, two PD series were identified: one series shows a loose dependence on temperature, and the other one a strong dependence. It was speculated that two types of defects may exist, whose geometry (and hence PD activity) may be affected by temperature to different extents (e.g., due to their position). Finally, a decrease in PD rate in time was observed, without a significant reduction of the average discharge intensity, which is supposedly due to different aging rates of different defects.

<span>Partial discharge (PD) pattern recognition is useful to diagnose insulation condition. PD measurement data is commonly represented in phase-resolved partial discharge (PRPD) format. PRPD is useful as it provides a visible pattern for different PD source and various features can be extracted for PD pattern recognition. Shorter PRPD duration will enable more training data but the information in each data is less and vice versa. This works aims to investigate the effects of using very short duration PRPD data on the accuracy of PD pattern recognition. The results conclude that machine learning models such as Artificial Neural Network (ANN) and Support Vector Machine (SVM) are robust enough such that reduction of PRPD duration from 15-seconds to 1-second causes less than 5 % drop in the classification accuracy. However, this is only true for noise free condition. <span>When the same PD data is overlapped with random noise, the classification accuracy suffers a significant reduction up to 19%. Therefore, longer PRPD duration is recommended to withstand the effects of noise contamination.</span></span>

The measurement of partial discharge(PD) of several faults in gas-insulated system (GIS) is discussed. Phase-resolved PD patterns have been measured using three different PD detection measuring systems: according to the IEC 270 recommendations, a VHF/UHF measuring system with narrow band filtering, and the UHF measuring system with wide band filtering. PD patterns are compared using computer-based discrimination tools. The influence of the selected center frequency on the PD patterns is discussed for the narrow band VHF/UHF measuring system. The influence of the number and type of GIS components between the discharging defect and the capacitive coupler on the shape of the PD patterns is analyzed. For several GIS components the signal reduction is studied. It was found that the shape of PD patterns is independent on the used PD detection circuit and the propagation path of the PD signals. As a result, discrimination and classification of PD distributions of several studied defects are possible using digital tools.

This paper presents the space charge impact on the inception and propagation of electrical trees in cross-linked polyethylene (XLPE) insulation via simulations and experimentation. A 3D finite element analysis (FEA)-based modeling is proposed to simulate electrical trees via a needle embedded on the XLPE insulation. The proposed FEA model demonstrates the influence of the space charge magnitude and polarity on the initiation of partial discharges (PD). Then the critical parameters at the tip of an 8 µm. tree are to be examined. Experimentation is necessary to verify the simulation results acquired and study the mechanism of electrical trees at the inception and propagation stage. Therefore, in the experiment, a needle with a curvature radius of 5 µm. is embedded in the XLPE as a method of simulating defects, such as protrusions, voids, or cracks found in cable insulation. The power source supplies several high AC voltages on the 20 kV (rated voltage) cable under test for observing the inception and propagation behavior of the electrical trees. Phase-resolved partial discharge (PRPD) patterns are extracted at the inception and propagation stages of the electrical tree to determine the severity of the PDs occurring. A relationship is obtained for the PD magnitude with respect to the applied AC voltage while considering the positive and negative polarities of the PDs. This relationship then allows for the acquisition of the maximum electric field-tree length characteristics. The goal of the simulation of electrical trees is to provide the reader with a better understanding about the effect of space charge magnitude and polarity to comprehend the behavior of the treeing inception and propagation mechanisms. The injection and extraction of space charges is a complex phenomenon that requires further visualization through simulations. Therefore, the results of both the simulation and experiment are compared with the aim of establishing a clear relationship between space charge distribution and tree initiation.