On-line Partial Discharge Measurements Research Articles

Novel Reference Method for the Characterization of PD Measuring Systems Using HFCT Sensors.

During their lifespan, high-voltage (HV) electrical systems are subjected to operating conditions in which electrical, mechanical, thermal and environmental-related stresses occur. These conditions over time lead to unforeseen failures caused by various types of defects. For this reason, there are several technologies for measuring and monitoring the electrical systems, with the aim of minimizing the number of faults. The early detection of defects, preferably in their incipient state, will enable the necessary corrective actions to be taken in order to avoid unforeseen failures. These failures generally lead to human risks and material damage, lack of power supply and significant economic losses. An efficient maintenance technique for the early detection of defects consists of the supervision of the dielectrics status in the installations by means of on-line partial discharge (PD) measurement. Nowadays, there are numerous systems in the market for the measurement of PD in HV installations. The most efficient with a reasonable cost will be those that offer greater security guarantees and the best positioned in the market. Currently, technology developers and users of PD measuring systems face difficulties related to the lack of reference procedures for their complete characterization and to the technical and economic drawback of performing the characterization tests on site or in laboratory installations. To deal with the previous difficulties, in this paper a novel method for the complete and standardized characterization of PD measuring systems is presented. The applicability of this method is mainly adapted for the characterization of systems operating in on-line applications using high-frequency current transformer (HFCT) sensors. For the appropriate application of the method, an associated and necessary scale modular test platform is used. In the test platform, the real on-site measuring conditions of an HV insulated distribution line are simulated in a controlled way. Practical characterizations, showing the convenience and advantages of applying the method using the modular test platform, are also presented.

Scale Modular Test Platform for the Characterization of PD Measuring Systems Using HFCT Sensors.

Today, online partial discharge (PD) measurements are common practice to assess the condition status of dielectrics in high-voltage (HV) electrical grids. However, when online PD measurements are carried out in electrical facilities, several disadvantages must be considered. Among the most important are high levels of changing electrical noise and interferences, signal phase couplings (cross-talk phenomena), and the simultaneous presence of various defects and difficulties in localizing and identifying them. In the last few decades, various PD-measuring systems have been developed to deal with these inconveniences and try to achieve the adequate supervision of electrical installations. In the state of the art, one of the main problems that electrical companies and technology developers face is the difficulty in characterizing the measuring system's functionalities in laboratory setups or in real-world facilities, where simulated or real defects must be detected. This is mainly due to the complexity and costs that the laboratory setups entail and the fact that the facilities are permanently in service. Furthermore, in the latter scenario, owners cannot assign facilities to carry out the tests, which could cause irreversible damage. Additionally, with the aforementioned installations, a comparison of results over time in various locations is not possible, and noise conditions cannot be controlled to perform the characterizations in a correct way. To deal with the problems indicated, in this article, an affordable scale modular test platform that simulates an HV installation is presented, where real on-site PD measuring conditions are simulated and controlled. In this first development, the HV installation comprises a cable system connected at both ends to a gas-insulated substation (GIS). As the most common acquisition technique in online applications is based on the placement of high-frequency current transformer (HFCT) sensors in the grounding cables of facilities, the test platform is mainly adapted to carry out measurements with this type of sensor. The designed and developed test platform was validated to assess its features and the degree of convergence with a real installation, showing the convenience of its use for the appropriate and standardized characterization of PD-measuring systems.

Metrological Qualification of PD Analysers for Insulation Diagnosis of HVDC and HVAC Grids.

On-site partial discharge (PD) measurements have turned out to be a very efficient technique for determining the insulation condition in high-voltage electrical grids (AIS, cable systems, GIS, HVDC converters, etc.); however, there is not any standardised procedure for determining the performances of PD measuring systems. In on-line and on-site PD measurements, high-frequency current transformers (HFCTs) are commonly used as sensors as they allow for monitoring over long distances in high-voltage installations. To ensure the required performances, a metrological qualification of the PD analysers by applying an evaluation procedure is necessary. A novel evaluation procedure was established to specify the quantities to be measured (electrical charge and PD repetition rate) and to describe the evaluation tests considering the measured influence parameters: noise, charge amplitude, pulse width and time interval between consecutive pulses. This procedure was applied to different types of PD analysers used for off-line measurements, sporadic on-line measurements and continuous PD monitoring. The procedure was validated in a round-robin test involving two metrological institutes (RISE from Sweden and FFII from Spain) and three universities (TUDelft from the Netherlands, TAU from Finland and UPM from Spain). With this round-robin test, the effectiveness of the proposed qualification procedure for discriminating between efficient and inappropriate PD analysers was demonstrated. Furthermore, it was shown that the PD charge quantity can be properly determined for on-line measurements and continuous monitoring by integrating the pulse signals acquired with HFCT sensors. In this case, these sensors must have a flat frequency spectrum in the range between several tens of kHz and at least two tens of MHz, where the frequency pulse content is more significant. The proposed qualification procedure can be useful for improving the future versions of the technical specification TS IEC 62478 and the standard IEC 60270.

A Study on the Effectiveness of Partial Discharge Models for Various Electrical Machines’ Insulation Materials

A vital component of electrical machines (EMs), which plays the most significant role in their reliable and proper operation, is their insulation system. Synchronous generators (SGs) are the most commonly used EMs in energy production and industry. Epoxy resin and mica are the predominant insulation materials for the SGs’ windings because their characteristics and properties are suitable for extending the lifetime of the insulation. Partial discharges (PDs) are both a symptom of insulation degradation, as they cause serious problems for insulation, and a means to identify possible insulation faults with offline and/or online PD tests and measurements. A comparison of three different equivalent circuit models of PDs occurring in different insulation materials (epoxy resin, mica, and a combination of these two) is presented in this paper. Different applied voltages and/or various geometries of voids are the factors investigated through simulations. The number of PDs, PD activity, and flashover voltages are examined in order to evaluate which of the aforementioned materials has the best reaction against PD activity.

Robust on-line partial discharge measurement of 35-kV cables in wind farms via dual sensors

Condition-based maintenance of cables in wind farms is critical for their operation reliability and stability. A promising solution to this task is to carry out on-line partial discharge measurement on the cables. However, impulse noise interferences from wind turbines or adjacent overhead lines could severely reduce the sensitivity of in field partial discharge measurement. Accordingly, this paper proposes a robust method to recognize the harmful partial discharge signal from the severe impulse noise. The method is based on joint analysis of the noisy partial discharge signals detected by two non-invasive partial discharge sensors, which are mounted on the double sides of the cable or on its terminal. The noiseless partial discharge signal and the impulse noise can be separated well via performing statistical clustering analysis on the pulse source location map or peak ratio vector obtained from the two detected noisy signal sequences. Finally, the effectiveness and feasibility of the proposed method is validated on two real partial discharge-affected 35-kV cables in an onshore wind farm.

Influence of Voltage Harmonics on Partial Discharge Diagnostics in Electric Motors Fed by Variable-Frequency Drives

Typically, in partial discharges (PD) diagnostics tests carried out in a laboratory, harmonic content in a voltage waveform is ignored. However, during the operation of variable-frequency drives (VFD)-fed electric motors, the distorted voltage waveform is produced due to the addition of harmonics components in the sinusoidal voltage waveform. The distortion level increases when the VFD is operated at a lower speed ratio. The additional spectral components in the applied voltage waveform can have a significant impact on the PD behavior in the insulation of the electric motor. Therefore, during online PD monitoring, overlooking the harmonic regime in the applied voltage may lead to a false interpretation of PD data. This article investigates the influence of voltage harmonics distortion produced during the variable-speed operation of VFD on PD characteristics. For this purpose, online PD measurements have been carried out by performing a series of experiments on eight VFD-fed motors under variable operating conditions. The PD severity at different harmonic compositions is experimentally investigated by determining various PD characteristic parameters including PD inception voltage, accumulated apparent charge, average discharge current, discharge power, and quadratic rate. Also, two terms Gaussian models have been mathematically developed using 288 data samples to quantify the variations in PD characteristic parameters against distortion parameters. The article proposes a framework for properly evaluating harmonics impact in PD for electric motors and correctly estimating stator insulation degradation.

Investigation of model transformer insulation behavior during PD activity in Di-Benzo-Di-Sulfide Sulphur contaminated transformer oil using online tan delta measurement

Sulphur can be present in mineral insulating oil and can manifest in stable, highly reactive and corrosive form. The corrosive sulphur reacts with the copper conductor in transformer and forms semi conductive copper sulphide at the surface of the copper conductor. The paper insulation used on the copper conductor may get damaged due to copper sulfide deposits which also affect the partial discharge activities prevalent in the transformer paper-oil insulation. The affect of Sulphur on model transformer paper-oil insulation is studied with online measurement of Dissipation factor (tanδ) and partial discharges (PD). The paper presents results of the investigatory work carried out with on-line tanδ and PD measurements made during experiments with Paper covered copper conductor (PCCC) in presence of Di-Benzo-Di-Sulfide contamination in transformer oil.

New model of explanation for phase angle pattern of online partial discharge measurement in winding insulation of turbine generator

Abstract On-line partial discharge (PD) measurement in electrical insulation of the turbine generator (TG) is an essential approach to control the quality of insulation and to avoid any undesired shutdowns of TG. Although in the last few decades the number of research in PD on-line monitoring methods in the stator winding of TG has increased significantly, it is still not clear yet why PD only appears at certain phase angles of the AC cycle in the phase resolved partial discharge (PRPD) pattern. Moreover, there is not yet any clarification on how the winding configuration of stator may affect PD phase angle pattern. For this reason, this work examines detailed study of the impact of the winding diagram on PD occurrence in the stator winding of real turbine generator class TVF-60-2 (60 MW, 10.5 KV). In addition, a computer simulation of various sizes of ellipsoidal cavities from 0.1 to 2.5 mm between conductor bar and stator core were carried out by using Laplaces equation in Finite Element Analysis (FEA) software ComSol to investigate the relation between the cavity size and coefficient of electric field. As a result of that, the phase angle of PD occurrence in the stator winding will highly depend on the configuration of bars connection, and the computer simulation has helped identifying the PD inception voltage and applied voltage of various ellipsoidal defects size. These two results have helped proposing an initial new theoretical model of explanation the relationship between voltage distributions and phase angle of PD occurrence to determine the degradation level of insulation caused by ellipsoidal defects in the insulation bars of the stator winding which can be used for stator windings of TG rated 6 kV and higher. This model is the initial step to develop a further comprehensive model of explanation for PRPD patterns which will consider all other types of defects as well as the space charge effects from the previous PD.

Turret-Electrode Antenna for UHF PD Measurement in Power Transformers - Part I: Introduction and Design

This contribution is the first part of a two-part series which deals with proposing a new type of UHF probe to overcome problems of UHF partial discharge (PD) measurement in power transformers. In the first part, the main obstacles of using the UHF technique in power transformers including problems of installation, unfeasibility of calibration, low sensitivity, etc. are addressed. Moreover, a new type of UHF sensor called the “Turret-Electrode” antenna is presented to deal with the above obstacles. In the new antenna, the transformer turrets employed as the housing of open waveguide antenna (horn antenna with zero flare angle), while an electrode inside of the turret is designed to capture the electromagnetic (EM) waves produced by the PD signals inside of the transformer tank. The significant characteristics of the proposed antenna are investigated in detail and a prototype of the antenna is investigated via practical measurements. The results show the antenna parameters are quite appropriate for online PD measurement. The second part of the paper shows how the proposed antenna can resolve the problems pertaining to the UHF PD measurement in power transformers.

A New Proposed Method for Interpretation On-line Partial Discharge Measurements Data of Turbine Generator

The online partial discharge measurements in the winding of turbine generator consider a widely used method for diagnosing the quality and evaluating performance of the stator winding insulation in turbine generator (TG). The present standards and technical specifications don't provide the interpretation that allows determining the size and location of the defects in the stator winding insulation of operating turbine generator. This paper discusses the results of features study of observing partial discharges (PD) in stator insulation when the TG is under actual operating conditions and proposes a new method for determining the size and the location of the defects in the stator bar insulation. Also it interprets the experimental results of the online PD measurement in turbine generator class TVF-60-2 (60 MW, 10.5 KV). The PD measurement data was monitored by PDViwe software and the PD ANALYZER-KSPEU software was developed and created to analyze and interpret the PD data by new proposed method. Additionally, the finite element analysis software ComSol was used to simulate the range of possible sizes and shapes of the cavity in stator winding insulation.

Modelling and simulation of online partial discharge measurement for medium voltage power cable

This paper presents the modelling of the online partial discharge (PD) measurement of the medium voltage (MV) power cable. Recently, PD monitoring trends are rapidly increasing due to high demand on reliable systems. Degradation are mainly due to the presence of PD in the high voltage power equipment used. PD measurement is therefore a highly recommended task to early detection of the degradation insulation for high voltage (HV) equipment in order to avoid breakdowns. Real network modelling is necessary to improvise system design in order to find the efficiency in a real power system network. In this paper, modelling focuses on a real distribution network by applying Rogowski coil (RC) as a detection sensor to trigger PD activity. The simulation is performed to determine the functionality and reliability of the system with the RC application in the network. The analysis is performed in the ATP-EMTP and MATLAB Simulink software environments. In addition, this paper contributed to justify the approach of a simplified PD sensor and measurement system. This PD measurement system provides a complete solution in the context of condition-oriented monitoring for the ability to apply the RC to trigger PD activity in the power distribution network.

Separation of Partial Discharge Sources Measured in the High-Frequency Range with HFCT Sensors Using PRPD-teff Patterns.

During the last two decades, on-line partial discharge (PD) measurements have been proven as a very efficient test to evaluate the insulation condition of high-voltage (HV) installations in service. Among the different PD-measuring techniques, the non-conventional electromagnetic methods are the most used due to their effectiveness and versatility. However, there are two main difficulties to overcome in on-line PD measurements when these methods are applied: the ambient electric noise and the simultaneous presence of various types of PD or pulse-shaped signals in the HV facility to be evaluated. A practical and effective method is presented to separate and identify PD sources acting simultaneously in HV systems under test. This method enables testers to carry out a first accurate diagnosis of the installation while performing the measurements in situ with non-invasive high-frequency current transformers (HFCT) used as sensors. The data acquisition in real-time reduces the time of postprocessing by an expert. This method was implemented in a Matlab application named PRPD-time tool, which consists of the analysis of the Phase-Resolved Partial Discharge (PRPD) pattern in combination with two types of interactive graphic representations. These graphical depictions are obtained including a feature parameter, effective time (teff), related to the duration of single measured pulses as a third axis incorporated in a classical PRPD representation, named the PRPD-teff pattern. The resulting interactive diagrams are complementary and allow the pulse source separation of pulses and clustering. The effectiveness of the proposed method and the developed Matlab application for separating PD sources is demonstrated with a practical laboratory experiment where various PD sources and pulse-type noise interferences were simultaneously measured.

Improved density peak clustering for separation of multiple source partial discharge in large generators

Multiple source partial discharge (PD) separation is indispensable in on-line PD measurements, particularly for large generators. For this purpose, an improved density peak clustering algorithm for the separation of a multi-source PD is presented. DPC is characterized by the selection of cluster centers from the decision graph labeled by local density and distance, while human involvement hinders its application toward automatic analysis. For complex PD data sets, the boundary between cluster centers and non-center points is often so fuzzy on the decision graph that the results are affected by human subjectivity. To overcome these drawbacks, an improvement to the determination method for cluster centers is presented, which is a key link in clustering. Based on the decision graph, a decision quantity is developed by multiplying the local density and distance. The local density peak points, with the decision quantity meeting specific criterion, are roughly defined as potential cluster centers, then the exact cluster centers are finally determined based on the defined density-reachable relationships between the potential cluster centers. The results of actual PD data sets demonstrate the effectiveness of the proposed algorithm and reveal the ability to separate PD data sets of arbitrary shape or uneven density, indicating the wide applicability prospects of the technique.

Partial Discharge Classification Using Deep Learning Methods—Survey of Recent Progress

This paper examines the recent advances made in the field of Deep Learning (DL) methods for the automated identification of Partial Discharges (PD). PD activity is an indication of the state and operational conditions of electrical equipment systems. There are several techniques for on-line PD measurements, but the typical classification and recognition method is made off-line and involves an expert manually extracting appropriate features from raw data and then using these to diagnose PD type and severity. Many methods have been developed over the years, so that the appropriate features expertly extracted are used as input for Machine Learning (ML) algorithms. More recently, with the developments in computation and data storage, DL methods have been used for automated features extraction and classification. Several contributions have demonstrated that Deep Neural Networks (DNN) have better accuracy than the typical ML methods providing more efficient automated identification techniques. However, improvements could be made regarding the general applicability of the method, the data acquisition, and the optimal DNN structure.

Partial discharge signal self-adaptive sparse decomposition noise abatement based on spectral kurtosis and S-transform

PurposeNoise abatement is one of the key techniques for Partial Discharge (PD) on-line measurement and monitoring. However, how to enhance the efficiency of PD signal noise suppression is a challenging work. Hence, this study aims to improve the efficiency of PD signal noise abatement.Design/methodology/approachIn this approach, the time–frequency characteristics of PD signal had been obtained based on fast kurtogram and S-transform time–frequency spectrum, and these characteristics were used to optimize the parameters for the signal matching over-complete dictionary. Subsequently, a self-adaptive selection of matching atoms was realized when using Matching Pursuit (MP) to analyze PD signals, which leading to seldom noise signal element was represented in sparse decomposition.FindingsThe de-noising of PD signals was achieved efficiently. Simulation and experimental results show that the proposed method has good adaptability and significant noise abatement effect compared with Empirical Mode Decomposition, Wavelet Threshold and global signal sparse decomposition of MP.Originality/valueA self-adaptive noise abatement method was proposed to improve the efficiency of PD signal noise suppression based on the signal sparse representation and its MP algorithm, which is significant to on-line PD measurement.

A Review of Online Partial Discharge Measurement of Large Generators

Online partial discharge (PD) measurements have long been used as an effective means to assess the condition of the stator windings of large generators. An increase in the use of PD online measurement systems during the last decade is evident. Improvements in the detection capabilities are partly the reason for the increased popularity. Another reason has been the development of digital signal processing techniques. In addition, rapid progress is being made in automated single PD source classification. However, there are still some factors hindering wider application of the system, such as the complex PD mechanism and PD pulse propagation in stator windings, the presence of detrimental noise and disturbances on-site, and multiple PD sources occurring simultaneously. To avoid repetition of past work and to provide an overview for fresh researchers in this area, this paper presents a comprehensive survey of the state-of-the-art knowledge on PD mechanism, PD pulse propagation in stator windings, PD signal detection methods and signal processing techniques. Areas for further research are also presented.

Measurement of PD in Operating Motors Fed by Voltage Source PWM Drives

On-line partial discharge (PD)measurement is now widely applied to motors rated 6 kV and above that are fed from the 50/60 Hz power system. However, many motors are being powered from invertors which facilitate variable speed motors to improve process efficiencies. One of the most common drives now being used is of the voltage source, pulse width modulation (VS-PWM) type. Such drives generate high voltage spikes in the kV range with risetimes in the submicrosecond range. These high voltage spikes are a form of severe electrical interference which render the detection of PD (with magnitudes 1000 x smaller) difficult, due to the overlapping frequency content in PD and the spikes. Thus PD detection on VS-PWM has been a challenge, in spite of the serious insulation aging that such drives may cause. This paper will outline the challenges in measuring the stator winding PD in motors fed by VS-PWM drives and describe a measurement system that is often effective. Results from measurements obtained using this system will be presented.

A System Based on Artificial Neural Networks for Automatic Classification of Hydro-generator Stator Windings Partial Discharges

Partial discharge (PD) monitoring is widely used in rotating machines to evaluate the condition of stator winding insulation, but its practice on a large scale requires the development of intelligent systems that automatically process these measurement data. In this paper, it is proposed a methodology of automatic PD classification in hydro-generator stator windings using neural networks. The database is formed from online PD measurements in hydro-generators in a real setting. Noise filtering techniques are applied to these data. Then, based on the concept of image projection, novel features are extracted from the filtered samples. These features are used as inputs for training several neural networks. The best performance network, obtained using statistical procedures, presents a recognition rate of 98%.

Novel inductive sensor solutions for on-line partial discharge and power quality monitoring

Networks of medium voltage have spread over a long distance through underground cables. The aim to prolong the life span of existing network assets increases the need for condition monitoring to prevent unplanned and long lasting interruptions. Continuous on-line partial discharge (PD) measurement is an excellent way to determine the overall health of the medium voltage (MV) components and to detect developing faults in underground cables. A sensor is an essential part of the PD monitoring system which measures the high frequency PD signals. PD sensors can be used to measure power frequency current and harmonic currents on the MV side to estimate the thermal loading of transformer or incoming cable provided that the sensors have a suitable frequency response for measuring low frequency signals as well. A novel inductive sensor is described in this paper which allows both PD measurements as well as power quality (PQ) measurements at frequency range below 2.5 kHz. Authors did experiments on different ferrite cores in order to design the best possible sensor which can be used for both PD and PQ measurement. Characteristics of the sensors, including sensitivity, saturation current, and frequency bandwidth, as well as relative errors are provided and analyzed under laboratory conditions. At the end, developed sensors are compared with a commercial HFCT sensor, the Rogowski coil and power quality current sensors to show the capability of the sensors to be used for PD and PQ measurements.

An Improved Directional Sensor for On-line Partial Discharge Measurement in Overhead Covered Conductors

Partial discharge is a symptom of the insulation condition of covered conductor lines and is effective for their predictive maintenance. Accordingly, there is increasing interest in identifying the traveling direction of partial discharge pulses in covered conductor lines in an effort to assist the location of the partial discharge source. In this article, a simple, convenient, and inexpensive sensor is designed to identify the traveling direction of partial discharge pulses. This improved sensor mainly consists of a pulse current transducer (an air-cored Rogowski coil) and a voltage coupler (two copper foil electrodes). The feasibility of this sensor is proven by software simulation and finally confirmed by both a pulse injection experiment and a high-voltage partial discharge test on a 10-kV cross linked polyethylene (XLPE) covered conductor.