Internal Partial Discharge Research Articles

Design and optimization for GIS UHF-Overvoltage composite sensor

Gas insulated switchgear (GIS) is widely used in power systems. Various built-in sensors have been designed to monitor internal partial discharges (PDs) and overvoltage, ensuring the safe operation of GIS. This paper presents a composite sensor for simultaneous measurement of PD and voltage, along with an effective optimization method that utilizes a Gaussian process (GP) surrogate model and self-adaptive evolution to optimize the complex composite sensors evaluated through simulations. The optimization method realizes accurate prediction of complex problems during the iteration with fewer training samples and is applied to the designed composite sensor, which requires determining additional parameters compared to the conventional sensors. Through iterations, the effective height of the composite sensor is significantly increased while maintaining a required measuring bandwidth. A test platform is constructed to assess the performance, and results demonstrate that the optimized sensor exhibits satisfying performance measuring both UHF PD signals and overvoltage in GIS. This study provides a design method for UHF-related sensors characterized by structural complexity.

Diagnostics analysis of partial discharge events of the power cables at various voltage levels using ramping behavior analysis method

Partial discharge events can occur in high-voltage cables. It can be caused by defects in the cable insulation, contamination, or a combination of both. Partial discharge in cables can lead to insulation failure and cable failure. This investigation aims to identify the trends and patterns in the internal partial discharge (PD) occurrences in the power cables when exposed to different voltage levels - 6.4, 7.4, 9.4, and 11.3 kV. For pattern extraction, a well-established method, ramping behavior analysis, is implemented to extract and classify PD occurrences into sets of significant and stationary events. In this investigation, significant events correspond to an absolute peak (the discharge pulse) and subsequent oscillations from the measurement sensor. The stationary events represent a collection of noise that is recorded during the measurement. These noise signals are essentially small variations within a pre-determined threshold range. Furthermore, a comparative analysis is performed for each voltage level and for the voltage levels.This investigation brings new knowledge on how internal partial discharge pulses occur at various voltage stress levels. Specifically, the emerging patterns and trends of internal partial discharge events. The results indicate that there is a positive correlation between the number of PD events and the increase in stress levels. Furthermore, negative PD peaks are more frequent at lower stress levels.

Ensemble Deep-Learning Model for Phase-Resolved Partial Discharge Diagnosis in Hydrogenerators

Condition monitoring of hydrogenerators is extremely essential for the optimisation of the power supply system’s maintenance, especially in a context where energy consumption will increase more and more. Industry investigations have consistently shown that the electrical insulation used in stator windings is one of the most potential components for breakdown. One of the major causes of this breakdown was shown to be partial discharges (PDs). PDs are designated as defects in electrical insulation, and their presence may cause future insulation failures in equipment. Online monitoring of PD activity is essential to anticipate degradation and avoid a sudden shutdown with a high economic impact. Thus, automating the recognition of PD sources by an intelligent system is a major issue in a Condition-Based Maintenance (CBM) process for hydrogenators. First, a method based on the U-Net model is used to isolate the main sources of a Phase-Resolved PD signal (PRPD). Afterwards, a set of deep learning models (DLM) is then applied to automatically recognize the PD sources. Finally, a decision-making method is then proposed to find the optimal output category considering the posterior and the prior probability estimated by various individual models. Experimental results on real signals from hydrogenerators show an accuracy of 87% on the detection of gap sources, and respectively 91%, 95%, 96% and 94% for the Internal, Corona, Slot and Delamination PD. The proposed decision-making method shows a significant advantage of the final decision over the performances of each individual DL model.

Application of a Rogowski Coil Sensor for Separating Internal and External Partial Discharge Pulses in Power Transformers

Partial discharge (PD) measurement is an essential tool for evaluating the health condition of a transformer insulation system. The Conventional PD measurement systems have a major drawback since they cannot discriminate the internal PD pulses and external pulse-shaped interferences, especially in online and on-site conditions. Various de-noising techniques (e.g. wavelets) have been also used in the literature, which is effective for extracting the PD signal from the noisy signals or classifying the PD types. However, the PD pulses and some of the randomly external pulse-shaped interferences have similar time-frequency characteristics, which makes them difficult to separate. In this paper, a new cost-effective and simple logic method is proposed for the separation of these interferences. This uses the polarity comparison of the output voltages of the Rogowski Coil (RC) sensor, mounted on the bushing, and measurement impedance, connected to the test tap. The same polarity represents the internal pulse, while the opposite polarity indicates the external pulses. A distribution transformer ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$20/0.4\ {\bm{kV}},\ 500\ {\bm{kVA}})$</tex-math></inline-formula> and a condenser bushing ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$72.5\ {\bm{kV}})$</tex-math></inline-formula> were considered to evaluate the performance of the proposed system. The results confirm the effectiveness of the proposed PD measurement system for separating the pulses.

A multi-resolution method for internal partial discharge simulation

Partial discharges and the electrical treeing represent one of key aspects for the ageing of the insulating parts of electrical components. To predict the end of life of dielectric systems several different modelling approaches have been developed. One of the most promising is the modelling using first principles and a set of partial differential equations. In this field, one of the toughest challenges is to cope with the very different scales of the treeing (each branch is a few micrometers wide) and of electrical components (raging from a few centimetres to a few meters).In this paper we propose an approach, based on the finite element and finite volume methods, which uses two completely independent grids to describe internal defects and electrical components. Some interpolation algorithms have been developed to couple the solution on the two grids. We have also tested the accuracy of our approach by comparing it with previously published methods that use only one grid.

FEA-Based Simulation of Accelerated Ageing in a Power Cable Due to Sustained Partial Discharge Activities in a Spherical Cavity

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.

Ensuring the reliability of turbogenerators on the basis of the control of discharge processes in the stator winding insulation

Issues related to the reliability of the electrical insulation system of high-load powerful turbogenerators with indirect gas cooling are considered and analyzed. The mechanisms of aging of the main components (main insulation, slot filling elements) of the insulation system under operating conditions exposed to electrical and thermal fields, and mechanical forces are studied. Modern ideas about the mechanisms of aging of main insulation and slot filling elements under the action of internal and external impacts (slot and spark discharges) are analyzed. The degradation of insulating materials during operation begins, first of all, in a weak local area of the main insulation, characterized by a large number of technological defects (cavities filled with gas), in which internal partial discharges occur. However, thermosetting insulation of high-voltage electrical machines can function normally throughout its lifetime in the presence of rather intense internal discharges. At the same time, no service life deterioration is observed due to the specific properties of modern main insulation, which contains a mica barrier. The greatest danger is posed by slot partial discharges (SPD) and vibration spark discharges (VS) that occur in the slot area of the stator winding. To reduce the intensity of these discharge processes, it is necessary to optimize the design of the anti-corona coating. On the basis of the performed analysis, a scheme was developed of the aging of the electrical insulation system of the stator winding of air-cooled turbogenerators. Based on the results of prototype tests, an estimated assessment of the "lifetime" of the electrical insulation system of the stator winding, developed using promising electrical insulating materials, was carried out.

Efficient condition-based maintenance of overhead distribution lines via partial discharge traveling wave detection

Fault diagnosis via partial discharge (PD) detection can timely identify and remove the deteriorating insulation, enhancing the persistence and resilience of power apparatuses. Visual and ultrasonic-based inspection method is a common manner to seek PD-affected power equipment in overhead distribution lines. However, the approach suffers from two deficiencies, inefficiency for widely distributed apparatuses or lines and ineffectiveness for internal PDs. An alternative solution is to use the travelling wave (TW)-based PD detection method, which can detect and locate PD in a remote distance. However, inconvenient installation and security problems of the conventional TW detectors impede their further application. Aimed at the limitations, the paper develops an improved TW-based PD detector for overhead distribution lines. Non-invasive and safe PD detection is achieved by a fiber optic transmission-enhanced Rogowski coils. Calibration of the PD detector is achieved via vector fitting technique and signal reconstruction. Finally, an on-site testing was carried out on a 5550-m PD-affected 10- kV overhead line and the result reveals that PD localization relying on the developed PD detectors can significantly improve the efficiency of PD measurement of overhead distribution lines.

Intelligent Online Partial Discharge Detection and Sensor

In order to realize the online monitoring of partial discharge in solid switch cabinet, obtain the real partial discharge power and evaluate the insulation status of the switch cabinet, an online detection device based on partial discharge in solid switch cabinet was proposed. The ultrasonic sensor and resonant circuit used by the device to collect the high frequency signal generated when partial discharge occurs and the high frequency signal was converted into the voltage signal. The voltage signal was sent to the STM32 main control chip after data preprocessing and analog-to-digital conversion. Through the conversion of the collected electrical data, the local discharge quantity was obtained and displayed on LCD screen in real time. If the detected discharge power was greater than a set value, an alarm would be automatically issued to remind the on-site power personnel to pay attention to it and prevent major power accidents caused by insulation damage. From the experimental results, it was found that the value of intermittent partial discharge collected by the developed device was 63pC, which was basically consistent with the DMS data. The experimental results showed that the device had the characteristics of simple operation and signal processing speed, high testing data real-time, and low cost, which was suitable for the real-time monitoring of the high voltage equipment in internal partial discharge. It was convenient for operators to maintain the equipment and ensure the normal operation of the equipment, which was of great significance to improve the reliability of power supply.

Long-term DC voltage test method of HVDC wall bushing with resin impregnated paper capacitor core considering electro-thermal coupling coefficient

HVDC wall bushing connects the valve hall and the DC field in the converter station, which is the core equipment in HVDC transmission system. The resin impregnated paper capacitor core inside the bushing withstands long-term full DC voltage and full load DC current during operation. Thus, 2 hours long-term DC voltage test and temperature rise test are required to verify its insulation and thermal performance. However, internal discharge faults caused by overheating of current carrying structure still occur frequently in recent years, which means the insulation and thermal defects of the bushing under long-term electrothermal coupling stress can not be completely inspected only IEC standard test. In this paper, the influence of temperature on internal partial discharge measurement and electrical field calculation of resin impregnated paper capacitor core of HVDC bushing are carried out, and the electro-thermal coupling coefficient is given. Finally, a new long-term DC voltage test method during manufacturing process is proposed. This new method has important theoretical significance and engineering application value for internal defect evaluation, discharge or thermal fault diagnosis, as well as estimation of the reliability of both insulation and thermal performance in the life cycle of bushing.

Research on discharge characteristics of GLA with surface pollution/icing

In operation of the AC power system, when the surface of gapped line arresters (GLA) is polluted, moist and iced, its internal electric field and potential distribution will be distorted. It will lead to the internal partial discharge and the significantly decrease of the power frequency discharge voltage, which seriously threatens the safety of the power system. Therefore, the influence on the body-gap voltage ratio of two typical structures of GLA under clean, polluted and iced external surface state need to be studied. And the finite-element method was used to calculate the electric field and potential distribution under different surface state. Based on the experiment of discharge characteristics of GLA under different conditions in artificial climate chamber, the electric field and potential distribution under the polluted and iced surface, the body-gap voltage ratio and the discharge characteristics of GLA were obtained, which was of great significance for the safety and stability of power system and the design of GLA.

Aging Performance of Low-Density Polyethylene/Silicone Rubber Blends Insulators Under Contaminated Conditions

Insulation materials are a vital part of the electrical system in all kinds of high voltage (HV) Transmission lines. Environmental stresses affect the performance of all types of insulation materials over time. Dielectric breakdown strength (DBS), Hydrophobicity, Leakage current, internal partial discharge and volume resistivity are all three degraded parameters in the service environment. The materials stand best in outdoor insulation, with the lowest partial discharge, highest breakdown strength, high hydrophobic, Lowest Leakage current, and highest volume resistivity. Enhancement of these parameters is a potential avenue for many researchers over the period. In this study, low-density polyethene (LDPE) under different nanofillers, including SiO2, TiO2, TiO2@SiO2, with different weight percentages, are used. This study investigates the behaviour of dielectric breakdown strength (DBS), Hydrophobicity and Leakage Current (LC) for 1000h test under contaminated conditions such as High voltage, heat, ultraviolet (UV) radiations, salt fog, humidity, and acid rain.

Integrated Method of Assessment the Type of Damages, their Localization and Predicting the Destruction of High-Voltage Electrical Equipment Insulators by the Partial Discharges Characteristics

The aim of this study is to improve the accuracy of localization of defects in insulators and determine their type. This goal is achieved by solving the problem of combining contact and remote methods for polymer and porcelain insulators using model partial discharges. The most significant results are the regularities of the dynamics of the characteristics of partial discharges up to the prebreakdown situation for porcelain insulators, the study of the statistical distributions of partial discharges depending on their intensity, and the identification of the features of the statistical distribution of surface discharges. Part of the work is devoted to the study of the characteristics of partial discharges and their sources by spectra, polarity, statistical distributions, oscillograms, which is important from the point of view of automating the recognition of corona and internal partial discharges, as well as for the recognition of porcelain insulators destroyed by partial discharges. Regularities of changes in the statistical distribution of partial discharges up to the pre-breakdown situation were established. At the same time, the breakdown signs of the model discharge gap, the breakdown voltage values for defective and operable porcelain insulators are determined, which can be used to train models of artificial neural networks and recognize the pre-breakdown situation based on them. The most significant results were: assessment of the ohmic resistance of porcelain insulators by the characteristics of partial discharges, recognition of corona, internal and surface partial discharges of polymer insulators, localization of defects, using electromagnetic radiation sensors.

Exploration on Automatic Management of GIS Using TL-CNN and IoT

The research aims to effectively monitor the state of complex industrial equipment in real time, diagnose the internal Partial Discharge (PD) pattern of Gas Insulated Metal Enclosed Switchgear (GIS), implement effective health management, and change the traditional model optimization route of increasing training time in exchange for performance improvement. This paper studies the complex equipment-oriented Health Management System (HMS) based on Internet of Things (IoT) technology and Transfer Learning. Firstly, the principles of Transfer Learning and Deep Learning (DL) technology are introduced. Secondly, the requirements of GIS internal status recognition and management are studied. Furthermore, a GIS-oriented HMS based on Transfer Learning-optimized Convolutional Neural Networks (CNN) is proposed, and the training dataset is constructed. Finally, the proposed model is tested. The results show that the complex equipment-oriented HMS based on IoT technology, CNN, and Transfer Learning can detect the internal status of GIS in real time. Compared with the traditional DL algorithm and expert system, the proposed model has a shorter training time of only 16min, faster convergence speed, high testing recognition rate, and over 96% recognition rate. Compared with other mainstream algorithms, it has higher identification, the storage parameter volume is 408, and the storage space is 12.8MB. Moreover, the proposed Transfer Learning-optimized CNN model can accurately detect the status of GIS, identify abnormal statuses, and help prolong the service life of GIS. The proposed complex equipment-oriented HMS contributes to the intelligent manufacturing industry and provides a new direction for applying emerging Computer Technology in the intelligent industry.

Real-Time Monitoring of the Vacuum Degree Based on the Partial Discharge and an Insulation Supplement Design for a Distribution Class Vacuum Interrupter

The internal pressure of a vacuum interrupter (VI) is increased by arc heat, ceramic cracking, gas leakage, and manufacturing defects. Accordingly, the dielectric strength of VI rapidly decreases. To improve the reliability of power transmission, efficient maintenance through the real-time monitoring of the vacuum degree is essential. However, real-time monitoring of the vacuum degree is difficult, and related research is scarce. Additionally, due to the insulation problems of this technology, there are few commercially available products. Therefore, this paper proposes a method for real-time monitoring of the vacuum degree and an insulation supplement design for a distribution class VI. First, dielectric experiments were conducted to identify the section in which the dielectric strength of the VI rapidly decreased according to the vacuum degree. Second, for real-time monitoring of the VI, several factors were proposed through the partial discharge in the VI, while the capacitance characteristics of the VI were calculated to improve the signal of the internal partial discharge. Finally, to supplement the dielectric problems of the solid insulation high voltage apparatus that occur when real-time monitoring technology is applied, the insulation supplement design was performed through the finite element method (FEM).

An uncoupled implementation of the local mean energy plasma model

The study of cold plasma represents a very active field of applied physics with technical applications ranging from medical treatments to estimation of aging of electrical components due to internal partial discharges and treeing. In particular, the simulation of this category of plasma plays an increasingly important role since more and more complex, and technically relevant, configurations can be represented. Various kinds of models have been considered, one possible classification is relative to the way the electronic energy is computed. In the local electric field approximation a simple algebraic relationship is used which directly links the electric field strength to the electron energy. On the contrary, in the local mean energy approximation a proper differential equation is solved. In most cases this equation is coupled with a conservation equation which predicts the electron concentration. We will tackle this latter case and we will introduce a formulation capable of decoupling the electron density equation from the electron energy one. We will study the properties of the new formulation and we will build a proper numerical scheme capable of preserving, at a discrete level, these properties. Moreover, we will also discuss the existence of the discrete solution and test the performances of the scheme both in simple test cases, where an exact solution is known, and in a technically relevant configuration such as the formation of a treeing structure.

Characterization of Partial Discharge Activities in WBG Power Converters under Low-Pressure Condition

Many sectors, such as transportation systems, are undergoing rapid electrification due to the need for the mitigation of CO2 emissions. To ensure safe and reliable operation, the electrical equipment must be able to work under various environmental conditions. At high altitudes, the low pressure can adversely affect the health of insulating materials of electrical systems in electric aircraft. A well-known, primary aging mechanism in dielectrics is partial discharge (PD). This study targets internal PD evaluation in an insulated-gate bipolar transistor (IGBT) module under low-pressure conditions. The estimation of electric field distribution is conducted through 3D finite element analysis (FEA) using COMSOL Multiphysics®. The procedure of PD detection and transient modeling is performed in MATLAB for two pressure levels (atmospheric and half-atmospheric). The case study is the IGBT module with a void or two voids in the proximity of triple joints. The single-void case demonstrates that at half-atmospheric pressure, the intensity of discharges per voltage cycle increases by more than 40% compared to atmospheric pressure. The double-void case further shows that a void that is harmless at sea level can turn into an additional source of aging and couple with the other voids to escalate PD intensity by a factor of two or more.

A Finite Element Analysis and an Improved Induced Charge Concept for Partial Discharge Modeling

Although much work has been done and significant progress has been made on partial discharges (PD) measurement and detection techniques, this is not the case for PD modeling. Four types of internal PD modeling, in sequential order from first to last developed, are three-capacitance (abc), induced charge concept (ICC), finite element analysis (FEA), and Multiphysics models. The abc model is too simple to provide an understanding of the physical phenomena affecting PD. In contrast, Multiphysics models are immature. Multiphysics models require a high number of physical parameters that need to be experimentally determined, which is not a trivial task. Moreover, adjusting the physical parameters to achieve a good agreement between simulation results and measurement results for a specific geometry and dimension may not work for other geometries and dimensions. The FEA model, a relatively recent model, and the ICC model, which fall between the abc and Multiphysics models in terms of modeling complexity, can partly explain mechanisms and physical phenomena associated with internal PD. However, to the best of our knowledge, there is only one paper comparing ICC and FEA models for a case study; thus, further research is needed to elucidate various aspects of these two models. In this paper, 1) an improved ICC and a FEA capable of describing phenomena occurring during PD are developed, 2) both developed models are coded and implemented either in MATLAB or in COMSOL Multiphysics linked with MATLAB, and their simulation results are compared and analyzed, and 3) the influence of different parameters including void shape, void size, and void air pressure on PD parameters are studied.

Various Methods for Measurement of Resistive Leakage Current of Metal Oxide Surge Arrester

Metal Oxide Surge Arrester (MOSA) does not require any ordinary maintenance. But MOSA is get affected from ageing due to the effect of discharging impulse currents, uneven heating and internal partial discharges. A leading cause of deterioration is ingress of moisture. The degradation of MOSA also correlated with the ageing level of the arrester. This is called degradation under surge. The ageing level with the degradation of MO surge arrester or the leakage current of the surge arrester is related to each other. The leakage current is directly proportional to the ageing level. If the ageing level is raise, the leakage current also will increase. So, various methods for determination of the condition of ZnO surge arrester by means of measurement of the arrester leakage current are discussed. A MSCM method, which is based on leakage current of the surge arrester presented. The measuring instrument Leakage Current Monitor is also discussed.

Particularities of measuring partial discharges in stator windings insulation systems of high-voltage electrical machines

The purpose of the article is to provide potential tools that can make a significant contribution to the identification of partial discharges (PD). Different types of partial discharges occur in stator winding insulation and a few partial discharges may occur simultaneously. Internal partial discharges are electrical discharges that occur in voids in the insulation of the stator winding. In typical stator insulation systems that use epoxy bonded mica tapes, insulation degradation due to internal partial discharges is usually slow (many years or decades). External partial discharges (slot PD and surface PD in the end-winding) are more dangerous and lead to the destruction of the insulation in a short time (several months or years). Therefore, the identification of insulation defects is essential. The analysis of existing methods for identification of defects in the insulation of high-voltage electrical machines using the results of measuring the partial discharges characteristics is carried out. The advantages and disadvantages of each of the groups of identification methods are characterized. It is shown that among the models of knowledge representation in solving problems of diagnostics of insulation systems for high-voltage electrical machines, identification methods, including field tests using training samples, are among the most suitable ones. It is noted that detection of insulation defects and their identification cannot be carried out only by direct measurements of PD characteristics and other dielectric parameters (electrical resistance, dielectric loss, polarization index). For this, special computing programs based on pattern recognition methods should be used. Results are presented of identification of technological defects in the insulation of the stator winding at the stage of factory testing, obtained using the PD identification method developed by the authors