Partial Discharge Phenomena Research Articles

A Detailed Review of Partial Discharge Detection Methods for SiC Power Modules Under Square-Wave Voltage Excitation

Silicon carbide (SiC) power modules are increasingly being used in high-voltage and high-frequency applications due to their superior electrical and thermal qualities. However, the issue of the partial discharge (PD) phenomenon raises serious reliability difficulties resulting in insulation failure, performance degradation, and potential device collapse. This paper provides a thorough assessment of the current PD detection strategies in SiC power modules. The issues provided by SiC devices’ distinct operational features, such as high switching frequencies and higher voltage stresses, which hinder PD detection and mitigation, are widely investigated. This review compares the effectiveness, benefits, and limitations of various detection methods, emphasizing the need for better strategies to ensure long-term reliability and performance. This study gives an in-depth overview of the numerous forms of PD phenomena that occur in power modules, including internal and surface discharges, as well as how they appear under various detection systems. It examines the performance of several methods for power module technologies such as SiC. To address these PD issues, this article proposes ways to improve reliability and detection accuracy.

Research and Simulation of Partial Discharge Phenomenon Sensing Technology for Substation Inspection Robots

Abstract This paper thoroughly investigates the phenomenon of partial discharge in substations and proposes a set of simulation experimental apparatus to replicate various types of partial discharge defects in switchgear. By modifying the switchgear, incorporating models for different types of partial discharge, and equipping various standard partial discharge sensors, accurate simulations of phenomena such as point discharge, suspended discharge, gap discharge, and particle discharge are achieved. Through this system, the effectiveness of different detection methods, such as ultrasonic, high-frequency, and transient voltage methods, is validated for various defect models. Furthermore, utilizing an indoor inspection robot guide rail, the paper simulates the environment of partial discharge in substations, enabling the validation of the robot’s partial discharge detection performance and typical patterns under different conditions. This work is dedicated to providing situational awareness technology for partial discharge phenomenon detection for substation inspection robots, so that the inspection robot can detect various abnormal partial discharge phenomena in transformers or other substation equipment through micro sensors to promote the stable operation of the substation.

Localization of Dual Partial Discharge in Transformer Windings Using Fabry–Pérot Optical Fiber Sensor Array

The power transformer is one of the most critical core devices for energy exchange in power systems, and its safe and stable operation is directly related to the reliability of the power grid. Partial discharge is the main cause of insulation degradation and failure of high-voltage electrical equipment. Online monitoring and accurate localization of partial discharge can provide information on the aging of power equipment, which is of great value for improving the safe operation and maintenance of the power grid. Internal dual partial discharge in transformer windings is a more complex type of fault. Since it is located inside the windings, the signal is attenuated and distorted, making it difficult for traditional monitoring methods to capture such partial discharge signal The Fabry–Perot optical fiber sensor is an ultrasonic detection method that can be built into the transformer interior. This sensor has high sensitivity and a small size, enabling flexible placement at different locations inside the transformer for precise partial discharge detection. Especially for the narrow space inside the high and low voltage windings, F–P sensors can form an array, utilizing the array’s directivity to locate the fault points. In this study, an ultrasonic detection system based on the F–P optical fiber sensor array was developed. The system utilizes a directional cross-localization algorithm based on the multiple signal classification (MUSIC) algorithm to accurately locate dual partial discharge sources. This partial discharge detection system was applied to a 35 kV single-phase transformer, enabling the localization of dual partial discharge sources within the high and low voltage windings. Combined with experimental results, this method exhibits high localization accuracy and is particularly suitable for detecting partial discharge phenomena that occur within or between transformer windings.

Investigation of Partial Discharge Phenomena on XLPE Cable Insulation Using COMSOL Multiphysics

The presence of various defects including the presence of micro-cavities, cracks, and contamination of impurities intensifies the field stress inside the insulation when subjected to high voltage (HV), which results in the initiation of discharge activity. Therefore, the measurement and analysis of partial discharge (PD) phenomena are essential for the condition assessment of HV insulation. This study focused on the application of COMSOL multi-physics in an XLPE cable insulation sample with an artificially created cavity defect to evaluate the distribution of electric field stress, PD inception, and extinction phenomena. The COMSOL simulation of the XLPE sample is carried out in the presence of a spherical void by considering the effect of void diameter, void position, and influence of harmonics. The study also replicates the influence of varying harmonic content along with total harmonic distortion (THD) which highlights the importance of PD pattern. It has been observed that PDs tend to concentrate in ( dE co ( t ) / dt ) , particularly in areas with significant slopes. Whereas, local minima act as inhibitors, and distorted the PD pattern which is 300% and 200% higher in 5th and 7th harmonic as compared to 3rd during 20% THD.

WITHDRAWN: Design of partial discharge measurement model for internal cavities in high voltage power cables

The phenomenon of partial discharge (PD) in power cables can result in insulation degradation and eventual failure if left undetected and unaddressed. As a result, the measurement of PD is key to evaluating the performance of insulation diagnostics in the power cables. This paper presents a PD measurement model for internal cavities in XLPE insulating material for medium voltage power cables. The proposed PD measurement model is designed using the COMSOL Multiphysics software as a finite element analysis (FEA) tool added to MATLAB environment, specifically tailored for power cables. The proposed PD measurement model uses the multiphysics capabilities of COMSOL to simulate the electrical discharges behavior within power cables. The model considers factors such as cable geometry, material properties, cavity size, applied voltage and numerical conditions to accurately capture the PD characteristics. Distributions of both electric potential and electric field were studied before and after occurrence of PD across the internal cavity. According to the results, it has been noticed that the discharge magnitude mainly depends on the cavity diameter; as increasing cavity diameter leads to increasing the magnitude of the measured PD. Moreover, the leakage current magnitude is recorded during the PD event period. The proposed model also enables the evaluation of different cable designs, insulation materials, and operating conditions to optimize cable performance and mitigate PD risks.

Study of partial discharge and breakdown phenomena at triple junctions under various conditions of pressure and temperature

The presence of a triple junction constitutes a potential source of failure in many industrial applications. The reinforcement of the local electric field due to differences in relative permittivity facilitates the formation of partial discharges (PD) which weaken the insulation system and eventually lead to complete breakdown. Additionally, severe environmental conditions (temperature, pressure) associated with certain applications (e. g. nuclear or aeronautical sector) should be considered because of their influence on discharge phenomena occurring at triple junctions. In this study, the behaviour of partial discharge inception voltage (PDIV) and of breakdown (flash-over) voltage (BIV) is compared in the case of a triple junction with an aluminium oxide disc as a solid insulator when the system is heated up to 400 °C. While the PDIV decreases strongly for temperatures above 300 °C, this effect disappears for the BIV. It is proposed that this behaviour is due to the fact that relative permittivity of the aluminium oxide disc increases with temperature at low frequencies, but remains relatively stable at high frequencies, regardless of the temperature.

Research on a Partial Discharge Expert System for the Diagnosis of Damaged Transformation Equipment

Partial discharge (PD) characteristics are very important for the diagnosis of damaged transformation equipment. If the power transmission and transformation equipment fails, it will cause large economic losses, and thus prevention is better than treatment. One of the effective methods for high-voltage insulation degradation detection is to observe the phenomenon of partial discharge of equipment, which is the earliest characteristic. Prevention can be carried out in advance, and trend observation is better than periodic inspection. Long-term observation can effectively reduce the probability of misjudgment. This project intends to develop a high-speed data-acquisition device to acquire the original discharge waveform data of partial discharge for noise suppression. In order to improve the diagnostic efficiency and accuracy of the diagnostic system, it is necessary to suppress the noise of the measurement data, so as to carry out the fault identification of the discharge type. Through this method, the actual operating data of the system can be recorded as the original discharge waveform, in order to understand the original discharge waveform conditions of the power transmission and transformation equipment in multiple partial discharge measurements, and then after noise suppression, it can be regarded as a type of partial discharge identification.

On-Line Partial Discharge Monitoring System for Switchgears Based on the Detection of UHF Signals

Aiming at the phenomenon of partial discharge caused by the insulation fault of switchgears, an ultra-high frequency (UHF) partial discharge online monitoring system based on the Internet of Thing (IoT) is designed. The hardware of the system mainly consists of UHF sensors, signal conditioning circuits, and data acquisition circuits to realize the monitoring of the discharge signal. The monitoring data is uploaded to the cloud platform through the 4G DTU module, and the host computer software based on B/S architecture is designed on the server side, which can monitor the operation status of the switchgear anytime and anywhere. The experimental results show that the detection system is stable and reliable and can meet practical needs.

Exploring the influence of powder particles in dielectric liquid of EDM: pulse train, discharge energy, material removal rate and surface topography

A comparative study on the effect of adding molybdenum di-sulphide (MoS2) powders of diameters 40 μm, 90 nm size into an ultrasonic vibration induced dielectric liquid of electrical discharge machining (EDM) process is attempted. Discharge duration, peak current, gap voltage are selected as input variables and their impact is assessed using pulse train, discharge energy, material removal rate (MRR) and surface integrity which are considered as outcome measure. The outcome measures of powder mixed dielectric (PMD) are compared with that of pure dielectric. Through pulse trains, a new phenomenon of partial discharge is identified. The incidence of partial discharge are assessed using scanning electron microscope (SEM) images. By varying the discharge duration, peak current and gap voltage, the discharge energy reduces in contrast to pure dielectric by 4%, 21.01%, 8.35% respectively for 40 μm diameter PMD and 10%, 27.29%, 17.99% respectively for 90 nm diameter PMD. The increase of peak current and gap voltage magnitudes cause the discharge energy to rise whereas discharge energy drops with growing magnitudes of discharge duration. Compared to the pure dielectric, the PMD produced enhanced MRR for similar discharge energy levels. The peak current has shown greater influence on MRR than discharge duration and gap voltage. In comparison with pure dielectric, the machining performance has improved by 21% for 40 μm diameter PMD, whereas 84.21% for 90 nm diameter PMD. At higher discharge parameters, better surface topography is produced in PMD than pure dielectric.

Variability of the Acoustic Emission Signals Generated by Partial Discharges in Mineral Oil

The main purpose of the presented research is to investigate the partial discharge (PD) phenomenon variability under long-term AC voltage with particular consideration of the selected physical quantities changes while measured and registered by acoustic emission method (AE). During the research a PD model source generating surface discharges is immersed in the brand new insulation mineral oil. Acoustic signals generated by the continuously occurred PDs within 168 hours are registered. Several qualitative and quantitative indicators are assigned to describe the PD variability in time. Furthermore some long-term characteristics of the applied PD model source in mineral oil, are also presented according to acoustic signals emitted by the PD. Finally various statistical tools are applied for the results analysis and presentation. Despite there are numerous contemporary research papers dealing with long-term PD analysis, such complementary and multiparametric approach has not been presented so far, regarding the presented research. According to the presented research from among all assigned indicators there are discriminated descriptors that could depend on PD long-term duration. On the grounds of the regression models analysis there are discovered trends that potentially allow to apply the results for modeling of the PD variability in time using acoustic emission method. Subsequently such an approach may potentially support the development and extend the abilities of the diagnostic tools and maintenance policy in electrical power industry.

Application of a Phase Resolved Partial Discharge Pattern Analysis for Acoustic Emission Method in High Voltage Insulation Systems Diagnostics

An alternative method for analysis of acoustic emission (AE) signals generated by partial discharges (PD), based on a correlation between voltage phase run and AE pulses, so called phase resolved PD pattern (PRPD), is presented in the paper. PRPD pattern is a well-known analysis tool commonly used in such PD diagnostic methods as conventional electrical and UHF ones. Moreover, it yields various signal analysis abilities and allows a direct correlation indication between measurement results achieved using different methods. An original PRPD measurement methodology applied for AE method as well as some exemplary measurement results and further data analysis capabilities are presented in the paper. Also a comparative analysis of PRPD patterns achieved using various measurement methods and different PD source configurations have been investigated. All presented experiments were done under laboratory conditions using PD model sources immersed in the insulation oil. The main purpose of the presented research is to indicate an all-embracing analytical tool that yields an ability to direct comparison (qualitative as well as quantitative) of the AE measurement results with other commonly applied PD measurement methods. The presented results give a solid fundamental for further research work concerning a direct correlation method for AE and other described in the paper diagnostic techniques, mainly in order to continue PD phenomena analysis and assessment in real life high voltage apparatus insulation systems under normal onsite operation conditions.

Investigation of Partial Discharges within Power Oil Transformers by Acoustic Emission

This paper presents the authors’ multi-channel measurement systems designed and built to conduct research on partial discharge phenomena using the acoustic emission method. The systems provide real-time monitoring, recording of signals and analysis of recorded signals. The analysis is carried out in time, frequency, time-frequency and discrimination threshold domains. In particular, a descriptor with the ADC acronym is defined, which ranks the signals according to the so-called degree of advancement. Studies have been carried out, showing that for a single partial discharge source, when tested in parallel, using the electrical and acoustic emission methods, the ranking of the signals using this descriptor is identical to the ranking according to the value of the apparent charge introduced by sources. This paper presents the authors’ patented method of partial discharge location and identification in power oil transformers. The results of tests of power oil transformer at the test station, conducted in parallel with the electric method and the authors’ method, and the results of tests in three selected transformers carried out during ongoing in-situ operation using the authors’ method are presented. Based on these results, the authors make diagnoses of the condition of the insulation systems in the tested transformers. The inspections of these transformers confirm the diagnoses.

Partial Discharge Detection Method for Distribution Network Based on Feature Engineering

Partial discharge phenomenon of overhead lines in distribution network is usually caused by the concentration of local electric field inside or on the surface of electrical equipment. According to partial discharge problem, based on the characteristics of the project the use of a machine learning is proposed for distribution network overhead line partial discharge detection model, first using the characteristics of engineering to extract the signal characteristics of different sides characterization, then respectively using K neighbor algorithm and back propagation algorithm, support vector machine (SVM) classification algorithm test. Experimental results show that when machine learning algorithm is used to classify time domain characteristic signals based on the feature engineering selected in this paper, k-nearest Neighbor algorithm has better classification and recognition effect than back propagation algorithm and support vector machine algorithm, with accuracy rate of 97.20%, recall rate of 96.30% and F value of 96.73%. In the frequency domain feature recognition and classification, the k-nearest Neighbor algorithm has 98.95% accuracy, 99.42% recall rate and 97.61% F value. Compared with the back propagation algorithm and support vector machine algorithm, the K-nearest Neighbor algorithm has the highest detection accuracy in the frequency domain feature detection of partial discharge on overhead lines of distribution network.

The Design of local placement detector for cable accessories based on ultrasonic technology

In the process of cable transmission, the existence of air gap, tip, burr and other conditions will cause partial discharge phenomenon and lead to cable insulation aging, which can affect the safety of power transmission. Partial discharge detection can detect early insulation defects accurately, timely and efficiently. It is an ideal method to detect the occurrence of PD by ultrasonic wave which is the by-product of PD because it is less affected by electromagnetic interference. At the same time, a clamping device is designed, which is compact in structure, easy to carry and high in accuracy. This discharge detector can reduce the degree of external interference in the detection process, improve the accuracy of ultrasonic waveform, accurately identify whether partial discharge occurs, and alarm.

Plasma Dynamics-Based Modeling and Analysis of Partial Discharge in Voids Inside Insulation of Power Transformer

Partial discharge (PD) modeling in voids is being studied; earlier, however, most studies considered a simplified model with many adjustable parameters. In this article, a comprehensive comparative study is being done with possible void shapes in transformer insulation using a modified drift-diffusion model with single adjustable free parameter of the electron generation rate and considering the secondary ionization process. In simulation studies, plasma-dynamics-based models are used to better understand PD activity inside voids. A drift-diffusion model is used for investigating the PD phenomena inside air-filled voids of commonly found geometries, namely, cylindrical, spherical, and ellipsoidal, bounded by different insulating materials in power transformers. The model is applicable for all void shapes and material of insulation. PD inception field, residual field, space charge density, and other electrical properties are obtained, and all the possible parameters are incorporated in the model thus improving its accuracy. In this article, the effect of void shape and insulation material on the PD activity is obtained. The inception electric field at which the discharge initiates is found to be lowest in case of spherical void resulting in easy formation of plasma discharge. This study thus uncovers the physical mechanism of PD inside insulation thus helping in maintenance and optimum design of transformer insulation.

Analysis on the Performance of Micro and Nano Molybdenum Di-Sulphide Powder Suspended Dielectric in the Electrical Discharge Machining Process-A Comparison.

The significance of suspending molybdenum di-sulphide powder particles of two distinct mean size viz. Φ40 μm and Φ90 nm into the dielectric of electrical discharge machining is analysed. Crater geometry, surface crack density, skewness, kurtosis and chemical alteration of machined surfaces are considered as outcome measures. A numerical model using finite element analysis is developed to forecast crater geometry. To validate the proposed model, experiments are conducted by varying input parameters such as discharge duration, peak current, and gap voltage. In comparison with the experimental results, the proposed model predicts diameter of crater with an error of 3.34%, 7.32% and 2.76% for discharge duration, peak current and gap voltage respectively for Φ40 μm powder; similarly, 0.19%, 3.65% and 2.78% for Φ90 nm powder. Scanning electron microscope images, 2D roughness profiles and X-ray diffraction profiles are used to assess the partial discharge phenomena, surface crack density, skewness, kurtosis and chemical alteration of the machined surface. For all parameter settings, the Φ90 nm produced surfaces with lessened micro-cracks compared to Φ40 μm. The Φ90 nm creates surfaces with negative skewness and kurtosis less than 3. The deposition of MoS2 powder particle on the machined surface is revealed through X-ray diffraction analysis.

Investigation on combined effect of humidity–temperature on partial discharge through dielectric performance evaluation

The humidity role in the partial discharge (PD) inception mechanism is quite challenging, especially when considering the environmental temperature. Indeed, there is no general rule to explain the humidity effect on the PD phenomenon. In this paper, the PD activity in inter-turn insulation is experimentally investigated for different relative humidity (RH) conditions at three different ambient temperatures, that is, 30°C, 60°C, and 90°C. Partial discharge inception voltage (PDIV) is directly measured through a photomultiplier tube (PMT), whereas the tip-up tests are performed aiming at monitoring both dissipation factor (tanδ) and insulation capacitance (IC). These extra measurements (diagnostic dielectric markers) allow better assessing the insulation status. The adoption of the tip-up test enables the insulation properties measurement. Based on the tip-up tests’ findings, the interfacial polarization process starts at 75% RH under 60°C, while the high conductivity area is already formed at 75% RH when the ambient temperature is 90°C. The water film formation deduced from the tip-up test is then used to explain the trend of PDIV, and the validity is further proved by finite element analysis (FEA).

Detection Technology of UHF IoT Sensing Terminal Device Based on Cloud Edge Cooperation

Abstract The local release detection technology of traditional Internet of Things (IoT) sensing terminal equipment cannot realize the integration of the cloud and IoT edge, resulting in obvious local release detection errors and low technical sensitivity. To this end, a local release detection technology comprising ultra-high frequency (UHF) IoT sensor terminal equipment based on cloud edge collaboration is proposed. The transient earth voltage signal coupling module of the perception layer is used to collect data locally published by the device. This paper uses edge computing to reduce information redundancy. The cloud computing application layer adopts the time difference positioning method to realize the partial discharge detection of the UHF IoT sensor terminal equipment. When an abnormality occurs in the terminal equipment, an alarm is triggered. The experimental results show that the average accuracy of this method in detecting partial discharge is as high as 93.89 %. The detection time of this method is short and its detection time of partial discharge phenomenon is as low as 4 ms. The fitting effect of the proposed method is better in detecting amplitude and discharge and the two have a linear relationship. This method also has higher detection sensitivity, can detect the partial discharge of different types of terminal equipment, and its application effect is good.

Efficient Partial Discharge Detection by Plasmonic Photonic Crystal Fiber Sensor With Bimetallic Grating

In this article, a new approach for optical partial discharge (PD) detection in gas-insulted systems is introduced for the first time to the best of our knowledge. The suggested sensor is based on plasmonic D-shaped photonic crystal fiber (PCF). Further, bimetallic grating structure of Ag/Au is utilized to enhance the sensor sensitivity. For light detection, methyl-red-doped poly (methyl methacrylate) polymer (MR-PMMA) is used as a sensing material for its photochromic characteristics and its fast response to visible light radiation. At resonance, good coupling occurs between the surface plasmon mode and the core guided mode. The radiated light intensity reflects the charge magnitude of the occurred PD process which can be detected by calculating the shift in the resonance wavelength of the loss spectra. The structural geometrical parameters are studied to improve the sensing performance using full vectorial finite-element method. The proposed sensor achieves high sensitivity of 667 pm/mW<inline-formula> <tex-math notation="LaTeX">$\cdot $ </tex-math></inline-formula>cm^&#x2212;2 with a linear performance with the light intensity. Moreover, the proposed sensor has advantages of simple and compact design, fabrication feasibility, electromagnetic interference immunity, fast response, and high sensitivity relative to conventional PD detection techniques using electrical methods. The designed sensor can be also utilized for laboratory testing and it could be evolved to accomplish real-time detection of PD phenomenon in gas-insulted systems.

Impact of PWM Voltage Waveforms in High-Speed Drives: A Survey on High-Frequency Motor Models and Partial Discharge Phenomenon

The insulation system’s dielectric of the electric motor is very often subjected to severe electrical stress generated by the high dv/dt seen at the machine’s terminals. The electrical stress and high reflected wave transient overvoltage are even more evident in case of high-speed machines fed by high-frequency (HF) converters featuring very fast wide-bandgap devices. They are promoting the occurrence of partial discharges and consequently accelerate ageing. As this is serious issue and the main cause of the drive failure, it is important to analyse and characterise the surges at the motor terminals. Several HF models of motors have been proposed in the literature for this purpose. This article presents a survey on HF motor models, which is crucial in understanding and studying the most critical parameter identification and overvoltage mitigation techniques. Moreover, it offers a comparison of the models’ main features as well as a comparison with the experimental voltage waveform at motor terminals. A general overview of the partial discharge (PD) phenomenon is also provided, as it is favoured by HF operation and together with HF motor modelling provides key insights to the insulation ageing issue. In particular, an analysis of the effects of PWM waveform affecting insulation is given, as well as useful methods for developing strategies for the inspection and maintenance of winding insulation.