Partial Discharge Pulses Research Articles

Partial Discharge Signal Denoising with Recursive Continuous S-Shaped Algorithm in Cables

Partial discharge (PD) detection plays a vital role in on-line condition monitoring of electrical apparatus in the power systems. However, the noise of PD measurements significantly degrades the performance of detection algorithms. In this paper, we focus on developing an adaptive filtering technique for the PD denoising problem. Heretofore, there are just a few literature reviews addressing the PD denoising based on such a method. The proposed recursive continuous S-shaped (RCSS) algorithm integrates the advantages of recursive strategy and continuous S-shaped function into adaptive noise cancellation (ANC) system, yielding enhanced filtering performance. The proposed algorithm can tackle PD noises in both Gaussian and impulsive scenarios, which is easy to implement in practical applications. The convergence behavior is also analyzed. Extensive simulation and experimental results confirm that the proposed algorithm can address polluted PD pulses, even in excessively noisy conditions, resulting in smaller mean square error (MSE) as compared to other state-of-the-art algorithms.

Space-Charge Accumulation and Its Impact on High-Voltage Power Module Partial Discharge Under DC and PWM Waves: Testing and Modeling

Emerging applications of compact high-voltage SiC modules pose strong challenges in the module package insulation design. Such SiC module insulations are subjected to both high-voltage dc and pulsewidth modulation (PWM) excitations between different terminals during different switching intervals. High <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dV/dt</i> strongly interferes with partial discharge (PD) testing as it is hard to distinguish PD pulses and PWM excitation-induced interferences. This article covers both the testing and modeling of PD phenomena in the high-voltage power modules. A high <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dV/dt</i> PD testing platform is proposed, which involves a super-high-frequency (SHF) (SHF >3 GHz) down-mixing PD detection receiver and a high-voltage scalable square wave generator. The proposed method captures SHF PD signatures and determines PD inception voltage (PDIV) for packaging insulation. Using this platform, this article provides a group of PDIV comparisons of packaging insulation under dc and PWM waveforms and discloses discrepancies in these PDIV results with respect to their excitations. Based on these PD testing results, the article further provides a model using the space-charge accumulation to explain the PD difference under dc and PWM waveforms. Both simulation and sample testing results are included in this article to support this hypothesis. With this new model, the article includes an updated insulation design procedure for the high-voltage power modules.

Development of the accurate localization of partial discharges in medium‐voltage XLPE cables based on pulse reconstruction

A method of reconstructing the original partial discharge (PD) signal to improve the accuracy of PD localization in cross-linked polyethylene (XLPE) cables is presented here. XLPE cables, extremely sensitive to PDs, are the most popular underground cables in urban grids. The conventional PD localization methods, based on evaluation of the arrival times of PD pulses in the time domain, are negatively affected by the dispersion and attenuation of PD signals propagating in the power cable. A method for the accurate localization of PDs realized through inverse frequency domain modelling (IFDM) is presented here. The method, eliminating the systematic localization error caused by the dispersion and attenuation, significantly improves the localization accuracy. The locations of the PD are identified by comparing peak values of the initial PD signals reconstructed from different extracted pulses. A method for evaluating the propagation constant of the cable is also presented. The efficiency of the accurate localization method was verified by laboratory experiments. Besides, the inherent limitations of the conventional PD localization method for longer cable tests are discussed. The inevitable location error in the conventional methods does not exist in the new method.

Evaluation of Erosion Discharge Characteristics in Inclined Plane Tracking and Erosion Tests on Silicone Rubber under AC and DC Voltages

This paper investigates partial discharge (PD) characteristics that lead to the erosion of silicone rubber (SR) polymer under AC stress and DC stress of both polarities. The experiments are performed on high temperature vulcanized (HTV) SR material samples. The inclined plane test apparatus, constructed in accordance with IEC 60587 requirements, is employed to produce the surface partial discharges and the resulting accelerated aging of the specimens. Two commercial instruments are used to obtain the PD data. A concurrent analysis of visual observations of discharge and PD data is performed to classify discharges based on the severity of material degradation that each type causes. Three types of PD are identified and characterized using diagrams of charge magnitude versus time and a signal processing technique called time-frequency mapping. Individual pulse waveshapes of each type of discharge are also analyzed. PD pulse waveforms are analyzed according to their amplitude, energy, pulse width, and frequency spectrum. These pulse waveform parameters are evaluated and compared for the eroding discharge pulses under AC and DC voltage stresses. It is found that the stages of material degradation during IPT are related to the variations in discharge magnitude and the location of pulse clusters on the time-frequency maps.

Modelling of partial discharge pulse propagation in transformer windings using multi conductor transmission line modelling scheme

Power transformers are considered as an essential component in the electric power systems. They are placed in services in different circumstances like electrical, environmental and mechanical stresses, and through the progress of operation it can affect with various threats and hazards. Transformer failure should be diagnosed earlier in order to avoid its unsafe and unstable operation. The main reason for failure of insulation in power transformer is due to partial discharges. The partial discharge activity occurring in the transformer have to be identified earlier, afore it progresses into a complete discharge, otherwise it results in the maintenance of the device and causes loss of economic cost to the utilities. In this paper, multi conductor transmission line theory is used for the modelling of transformer windings and the partial discharge pulse propagation through the winding is simulated in the MATLAB Simulink. The effect of partial discharge on the windings are also discussed.

Achieving the exact equivalent circuit of a large-scale transformer winding using an improved detailed model for partial discharge study

Investigating partial discharge (PD) is a critical issue in monitoring the condition of power transformers. For analyzing the transient state behavior of transformer winding, the availability of a model that accurately presents its behavior at high frequencies is necessary. The conventional detailed model is among the models used to perform PD studies. One of the underlying issues of the conventional detailed model is the low frequency validity range of the model, which is limited to about 1 MHz. In this paper, an improved detailed model is presented that overcomes the mentioned problem by adding stray capacitances to the conventional detailed model. A general state-space algorithm is proposed to calculate the reaction of the winding towards the application of the PD signal. In the present study, the frequency-dependent parameters of the improved detailed model have been calculated via the finite element method (FEM). The new methods and ideas are implemented and validated on a real 20 kV distribution transformer winding as well as a 63 kV, 30MV winding. Comparing the results of the proposed model with the waveforms obtained from using PD pulses to both windings in the laboratory environment shows the accuracy and the increased frequency validity range of this model.

Trichel Pulse Analysis: Physical Calculation and Validation by Using Broadband Measurements

Partial discharge measurement is part of the monitoring of equipment in power engineering systems. It provides important information about the condition of the equipment and in particular the condition of the insulation components. This information serves to take necessary preventive measures at an early stage to avoid failures of the affected energy system and thus ensure a high level of energy supply security. Possible causes of partial discharges in energy technology equipment include high field strengths at edges with small radii or defects within insulation materials itself. Depending on the location and extent of the occurrence, partial discharge events may cause lasting damage to components of equipment. In order to be able to interpret the measurement results of partial discharge monitoring with regard to the exact cause and, if necessary, to evaluate them automatically, a precise understanding of the physical phenomena that occur during a partial discharge is necessary. The physical replication of a partial discharge pulse helps to better understand, evaluate, and interpret measurement results and thus create a synergy between measurement data and model-based results.

Wavelet method optimised by ant colony algorithm used for extracting stable and unstable signals in intelligent substations

Partial discharge (PD) signals are an important index to evaluate the operation state of intelligent substations. The correct distinction of PD pulse and interference pulse has become a challenging task. Because of the noise and the low signal-to-noise ratio, the stable signals become non-stationary. The selection of a wavelet basis, the selection rule of threshold λ and the design of the threshold function are the key factors affecting the final denoising effect. Therefore, an enhanced ant colony optimisition wavelet (ACOW) algorithm was applied to find the global optimal threshold through the continuous derivative threshold function and the ant colony optimisation (ACO) algorithm. At the same time the efficiency of adaptive search calculation, was also significantly improved. The method of the ACOW algorithm was compared with the soft wavelet method, gradient-based wavelet method and the genetic optimisation wavelet (GOW) method. Using these four methods to denoise four typical signals, different mean square errors (MSE), magnitude errors (ME) and time costs were obtained. Interestingly, the results show that the ACOW method can achieve the minimum MSE and has less time cost. It generates significantly smaller waveform distortion than the other three threshold estimation methods. In addition, the high efficiency and good quality of the output signals are beneficial to the diagnosis of local discharge signals in intelligent substations.

Error in the measurement of partial discharge pulses according to the frequency response of HFCT sensors

Error in the measurement of partial discharge pulses according to the frequency response of HFCT sensors

Current sensor optimization based on simulated transfer function under partial discharge pulses

The time measurement efficiency of the partial discharge (PD) relies on the signal-to-noise ratio (SNR) and gain of the high-frequency current transformer (HFCT) sensor. However, the PD's time measurement efficiency decreases with the noise coupled to the HFCT in onsite measurements. To overcome that setback, this paper proposes one pre-processing, through modelling and simulation, considering the physical effects, features of the electrical circuit and coil construction parameters of the HFCT. The main goal is to reach reasonable high SNR under the strong influence of background noises. This investigation aims to validate the hypothesis of improvement or deterioration of the HFCT signal response through a transfer function optimization. This research effort's contributions are threefold: 1. Generation of PD pulse signal and noise addition; 2. HFCT modelling, simulation, and frequency response analysis; and 3. Models performance evaluation and validation of hypothesis. In conclusion, the pre-processing approach stands out as a means to robustify and provide freedom to the electric utility, making up for an eventual need to redefine the physical and geometrical parameters of the HFCT sensor under specific background noise for maintenance tests purpose. According to a cyber-physical system framework, experiments corroborate the project's goals to contribute to the PD pattern monitoring in onsite measurements and incorporate robustness to signals with low SNRs.

Phase-resolved partial discharge analysis of different types of electrode systems using machine learning classification

Partial discharge (PD) measurement is a diagnostic technique used for electrical insulating systems. The establishment of a highly accurate PD diagnostic technique has become necessary in recent years. Therefore, in this study, we analyzed a phase-resolved PD signal using machine learning classification for different types of experimental electrode systems. A polyethylene sheet was used as the sample, and PD was generated by applying a high AC voltage to four different types of electrodes. The number of PD pulses was counted from the raw data as preprocessing to calculate the feature value for the machine learning. The PD generation rate was defined for each phase angle section. Four types of machine learning algorithms were adopted for the classification of the electrode system: k-NN (k-nearest neighbor algorithm), logistic regression, decision tree, and random forest. The best accuracy was obtained by using the random forest algorithm (0.97), and it was found that k-NN also demonstrated good performance. The parameter dependencies were also evaluated for each algorithm. Based on the results generated by the random forest, it became clear that there were phase angle sections that were of high importance. The reason for the result was discussed from the perspective of (i) the difference due to the electrical circuit parameters (modified abc-model) and (ii) the stochastic fluctuation of PD signal.

Partial discharge detection and identification at low air pressure in noisy environment

Increasing demand for electric power in more electric aircraft requires a higher operating voltage for the power system that leads to higher electric stress on the insulation system. Operating at high altitudes where the electrical strength of air is weakened exposes the insulation system to even higher levels of electrical stress. As such, the probability of partial discharges (PD), which result in insulation degradation and failure, is higher. The presence of switching circuits in the power distribution system of the more electric aircraft is capable of producing high levels of noise. This noise in combination with the background noise and parasitic impedances will cause high amplitude ringing in the measured partial discharge signal waveform. Here, a method based on the combination of the wavelet and energy techniques is employed to detect PD pulses in a noisy environment under the low air pressure condition. To verify the technique, a laboratory setup consisting of two separate PD sources mounted in low air pressure (33 kPa) chamber is developed where sine and square waveforms are used as the applied voltage. The obtained results demonstrate that the proposed approach offers low computational complexity, high performance in PD phase localization, and robustness in a noisy environment.

A novel wideband partial discharge measuring circuit under fast repetitive impulses of static converters

Nowadays fast switching power electronic devices are used for driving high voltage electric rotating machines. These power supplies apply sharp transient voltage at the time of switching. To study the effect of these stresses on the insulation system, investigating Partial Discharge (PD) during voltage rapid changes is of special interest. Although, the implemented coupling capacitor in a conventional PD measuring circuit provides a low impedance pass for the PDs, but imposes a transient current caused by sharp changes of voltage at the time of switching; hence, the measuring impedance of the conventional partial discharge equipment cannot distinguish an actual PD pulse from the mentioned transduced capacitive current pulses. Currently, two options are available in order to cope with this issue, including UHF technique and implementation of band pass filters. On the one hand, calibration of the PD pulses in the UHF method is not possible; hence, the PD test results of different manufacturers of machines under such stresses cannot be compared, which is the main drawback. On the other hand, one has to remove a wide range of frequency components of PD pulses that makes PD calibration procedure to be invalid. In this paper, a resonant full bridge topology is implemented to cancel out the capacitive pulse shaped current, where the PD pulses are captured directly via electrical method in a symmetric introduced configuration. The resulting inrush current has drastically reduced and a wideband measuring circuit with a true calibration process has become possible.

The effect of silica content to partial discharge characteristic of low-density polyethene and natural rubber blend as the electrical insulator

The dielectric properties of low-density polyethylene natural rubber (LDPE-NR) biopolymeric insulating materials can be improved by adding the silica nanoparticles in a certain percentage of weight (w%). In the present study, four types of bio-nano polymeric samples were prepared. To each sample, the nanosilica particles with wt% 1.5%, 3%, 4.5% and 6%. As one characteristic of dielectric, the partial discharge (PD) characteristics, each sample has been tested for 1 hour under AC high voltage field, and the pulses were counted for each sample and grouped into positive and negative pulses. The PD pattern was also plotted based on X-Y axes, namely Φ-q-n pattern. It was found that the number of positive and negative partial discharge (PD) pulses for each silica sample after 60 minutes of testing varied for all samples. It is also found that samples with a higher percentage of nanosilica had fewer PD pulses. The PD pattern in lower w% of silica was identified in the 90 degrees mostly in containing This indicates that w% of nanosilica particles can improve the PD resistance or the insulation quality of LDPE-NR insulation materials.

Partial Discharge Features for Power Electronic Transformers Under High-Frequency Pulse Voltage

Power electronic transformers (PETs) are becoming popular in the modern dc distribution grid due to their high efficiency and flexibility. To increase the power density of PETs, high-switching frequency would be adopted for the power switches. However, this may eventually increase the risk of partial discharge (PD) as the internal insulation space is reduced. In order to investigate PD characteristics in PETs under high-frequency pulse voltage, an experimental platform was set up in the laboratory, in which a twisted pair of wires model was used to test the insulation failure between windings in PETs. The PD behaviors were thoroughly investigated in the frequency range of 50 Hz to 20 kHz by time-resolved PD (TRPD). The results reveal that at high frequency, both the initial discharge voltage and discharge repetition would increase, while the PD amplitude decreases. Moreover, the PD pulses mainly occur at the field strength inversion of the rising and falling edges, the discharge time width tends to increase at high frequency. By analyzing the discharge model under pulse voltage, the discharge amplitude decrease and discharge times increase due to the difference of charge accumulation field intensity and effective discharge time at different frequencies. Under high-frequency voltage, the number of PD and the proportion of discharge time is much higher than 50 Hz, which may be the main reason for high-frequency insulation failure prematurely. According to the insulation life model based on the total discharge amplitude, the insulation life of 20 kHz is slightly higher than 10 kHz. When designing HFT, 20 kHz should be elected as operation frequency rather than 10 kHz.

WITHDRAWN: Analysis of partial discharge patterns of natural ester oil and mineral oil used in power transformer

Abstract The liquid insulation used for power transformer over the years is petroleum based mineral oil because of it availability and good electrical, chemical insulation properties. However because of its poor biodegradability, low flash point and concern over environment nowadays mineral oil has been replaced with biodegradable oil. Natural ester oil is made from natural substances like soyabean, which are environment friendly, almost fire proof and have great electrical insulation properties. Partial discharge is considered to be one of the main reasons for degradation of insulations in power transformers. In this paper comparative study of experimental results of partial discharge patterns of mineral and natural ester oil are discussed. The experimental setup was designed as per IEC Standard. Power transformer insulation is modeled as pigtail specimen and tested for partial discharge behavior by applying stress more than inception voltage of mineral and natural ester oil. Phase resolved partial discharge pattern are used to analyze the results. It was found that Natural ester oil has better inception voltage compared to mineral oil and also number of partial discharge pulses and PD magnitudes are less compare to mineral oil.

Characteristics of Creeping Discharge Caused by a Needle Electrode in Oil-Pressboard Insulation under +DC Voltage

This paper presents an analysis of the creeping discharge characteristics caused by a needle electrode in oil-pressboard insulation under a positive DC voltage. The discharge behavior under a strongly (model I) or weakly (model II) vertical component of the electric field is studied using partial discharge (PD) detections, camera observations, and charge distribution simulations. It is found that the development process of the creeping discharge can be divided into three stages according to the stepwise growth trends of apparent charge amplitude and PD repetition rate. The time-resolved PD pattern and equivalent time-frequency pattern are different in the two models. Most discharge pulses are unimodal with underdamped oscillations, but bimodal pulses can occur in model II. The streamer in model I has a tail caused by the stranded charge. A secondary streamer can occur in model II following the initial streamer, causing a bimodal PD pulse. The study findings can provide suggestions for the optimization of insulation design and the promotion of converter transformer maintenance.

Инновационные решения для измерения частичных разрядов

The article discusses systems developed using an innovative approach to measuring partial discharges, their advantages over traditional methods of monitoring cable lines and electrical equipment, as well as the principles of their operation. The design of the systems is based on a special broadband sensor-antenna which provides remote recording of both partial discharge pulses and the phase of alternating current flowing in the object of measurement without taking the equipment under test out of operation. Due to the wireless nature and system compact dimensions, partial discharge measurements can perform in previously inaccessible conditions, significantly expanding the capabilities of this diagnostic method. The partial discharge measurements are an up-to-date method for predictive diagnostics of cable systems and are necessary for the condition-based maintenance.

Towards Secured Online Monitoring for Digitalized GIS Against Cyber-Attacks Based on IoT and Machine Learning

Recently, the Internet of Things (IoT) has an important role in the growth and development of digitalized electric power stations while offering ambitious opportunities, specifically real-time monitoring and cybersecurity. In this regard, this paper introduces a novel IoT architecture for the online monitoring of the gas-insulated switchgear (GIS) status instead of the traditional observation methods. The proposed IoT architecture is derived from the concept of the cyber-physic system (CPS) in Industry 4.0. However, the cyber-attacks and the classification of the GIS insulation defects represent the main challenges against the implementation of IoT topology for the online monitoring and tracking of the GIS status. For this purpose, advanced machine learning techniques are utilized to detect cyber-attacks to conduct the paradigm and verification. Different test scenarios on various defects in GIS are performed to demonstrate the effectiveness of the proposed IoT architecture. Partial discharge pulse sequence features are extracted for each defect to represent the inputs for IoT architecture. The results confirm that the proposed IoT architecture based on the machine learning technique, that is the extreme gradient boosting (XGBoost), can visualize all defects in the GIS with different alarms, besides showing the cyber-attacks on the networks effectively. Furthermore, the defects of GIS and the fake data due to the cyber-attacks are recognized and presented on the dashboard of the proposed IoT platform with high accuracy and more clarified visualization to enhance the decision-making about the GIS status.

Comparing the New Improved RLC and CMTL Models for Measuring Partial Discharge in Transformer Winding

Nowadays, one of the most well-known methods for accurate simulation of the fast-transient phenomenon as well as the study and location of partial discharge (PD) in transformer windings is the method based on winding modeling. In this regard, the circular multi-conductor transmission line (CMTL) model, which is an improved model of the MTL model, has been proposed as the finest solution since it is acceptable in an extensive frequency range and it can investigate the effect of winding rotation by considering the radius and angle variables. However, one of the fundamental problems of using the CMTL model is that a set of large equations, known as complete admittance matrices, must be solved for all winding turns, which typically contain thousands of turns. To overcome this problem, we presented an improved RLC model, which has the same accuracy as the CMTL model in terms of frequency validity range and less computational complexity. In this model, the variables of length and curvature of the turns are also considered in the formulations. Although this method is theoretically accurate, its reliability method must also be determined in practice and how the PD signal propagation must be carefully considered due to the problems in high-frequency modeling of the winding. Numerical analyses and laboratory measurements resulting from the use of PD pulses on a 20 kV winding of a distribution transformer, as well as a 63 kV, 30 MV winding, revealed that a valid frequency range is extendable up to 5 MHz for the proposed improved model without a significant increase in computational complexity.