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This paper has a twofold aim. On one side, it aims to show a paramount application of an innovative approach to automatic partial discharge (PD) monitoring and analysis, referring to types of cable defects that can trigger internal and surface discharges. The type of defect generating PD is automatically identified, which is of fundamental importance to develop condition maintenance tools of any electrical asset component. On the other side, the way to create artificial defects, namely using a tool to test any PD measurement approach, is illustrated and discussed, relying upon partial discharge inception field and voltage modelling. Also, the so-called three-leg approach, which is capable of achieving the optimal and reliable design of electrical insulation systems, was applied and successfully validated for simple test objects and real electrical assets such as cable with artificially developed defects. [ABSTRACT FROM AUTHOR]

The environmental challenges associated with high-power, high-voltage electrified aircraft require a targeted approach with regard to the development of next-generation aerospace electrical insulation. This study reports findings on polyphenylsulfone (PPSU) as a matrix material based on its unique thermal, mechanical, and dielectric properties, filled with hexagonal boron nitride (h-BN) with micron- and nanoscale particulates. The inorganic ceramic filler was selected for its thermally conductive and electrically insulating performance in extreme environments. The main goal was to investigate the dielectric strength and electrical resistance (endurance) to partial discharges (PDs). Since PDs are a leading accelerated degradation phenomenon causing premature failure in organic electrical insulation, the capability of an insulating material to endure PD-induced degradation for the whole (or part of) its design life is of paramount importance. It was observed that incorporation of h-BN micro fillers can significantly improve the PD resistance, even in comparison with insulating materials typically used for electrified transportation, such as corona-resistant Kapton. It was also observed that a suitable combination of micro and nano fillers can also be used as a viable solution to increase the electrical performance and reliability of the avionics insulation components. [ABSTRACT FROM AUTHOR]

Medium-voltage (MV) cables often experience a shortened lifespan attributed to insulation breakdown resulting from accelerated aging and anomalous operational and environmental stresses. While partial discharge (PD) measurements serve as valuable tools for assessing the insulation state, complexity arises from the presence of diverse discharge sources, making the evaluation of PD data challenging. The reliability of diagnostics for MV cables hinges on the precise interpretation of PD activity. To streamline the repair and maintenance of cables, it becomes crucial to discern and categorize PD types accurately. This paper presents a comprehensive review encompassing the realms of detection, feature extraction, artificial intelligence, and optimization techniques employed in the classification of PD signals/sources. Its exploration encompasses a variety of sensors utilized for PD detection, data processing methodologies for efficient feature extraction, optimization techniques dedicated to selecting optimal features, and artificial intelligence-based approaches for the classification of PD sources. This synthesized review not only serves as a valuable reference for researchers engaged in the application of methods for PD signal classification but also sheds light on potential avenues for future developments of techniques within the context of MV cables. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) diagnostics test is a reliable solution for estimating insulation health conditions in power system components. During laboratory PD diagnostics, the effect of harmonic components in the voltage waveform generated by variable frequency drives (VFD) fed electric motors (EMs) is often overlooked. As VFD‐fed EMs operate at low speeds, the harmonic concentration in the voltage increases. It has been found that PD activity in VFD‐fed EM is significantly affected by the addition of harmonic components in the voltage, thus making it necessary to consider their impact when performing true PD diagnostics. This paper investigates the influence of voltage harmonic distortion produced in VFD‐fed EM on PD severity and the subsequent insulation degradation. Eight VFD‐fed EM are used to study the PD behaviour under different levels of harmonic pollution. The PD characteristics, such as inception voltage, pulse repetition rate, accumulated apparent charge, average discharge current, discharge power, and quadratic rate, are determined. Using probability distribution functions, PD activity and severity at various voltage harmonic levels are estimated. The proposed technique can be used to plan the maintenance activities that ensure the reliability for industrial applications dealing with the voltage harmonic distortion. [ABSTRACT FROM AUTHOR]

The partial discharge (PD) measurement is an important method used in determining the condition of medium- and high-voltage cable insulation. Considering the propagation velocity of PD signals in power cables is necessary for determining the location of PD defects. However, the determination of velocity is not straightforward due to propagation-related attenuation and dispersion, which distorts the PD pulse waveform. This introduces a degree of uncertainty into the pulse velocity as well as the PD source locations determined based on that velocity, which is usually considered to be of constant value in PD analysis. This paper investigates the accuracy of the pulse propagation velocity measurement in power cables. Tests were performed on a medium voltage power cable in a laboratory setting using two sets of PD-specific measurement equipment: a high-frequency current transformer (HFCT) and an IEC 60270-compliant conventional measurement system. The propagation velocities and their statistical variability were determined using both devices to assess the uncertainty of the propagation velocity measurement. The results indicate that the measured velocity is slightly higher in the case of the HFCT and that the 50% peak threshold value should be used rather than the peak value of PD sensor response waveforms to increase the precision of velocity measurements. [ABSTRACT FROM AUTHOR]

• Experimental study on medium voltage cable insulation under increasing electrical stress. • Development of an effective algorithm for detection of PD pulses in a PRPD pattern. • Analysis of measured PD data and correlation of PD characteristics. • Trending attributes of PD characteristics with increasing electrical stress. • Implementation of regression models to map trending behavior of PD characteristics. Insulation degradation in power components is a looming issue that can have a significant impact on the reliability of power system if not attended timely. Partial discharge (PD) diagnostics is a key technique used for the condition monitoring and health assessment of insulation. Inception of PD is a primary indicator which shows degradation and decreased local dielectric strength of the insulation. PD magnitude can increase with time and level of stress, which may result in failure of insulation. This article investigates the behavior of PD characteristics in a medium voltage (MV) cross-linked polyethylene (XLPE) cable sample, containing a defect at the cable termination, under elevated electrical stresses. PD behavior is studied by investigating the key PD characteristics, such as partial discharge inception voltage (PDIV) , phase of occurrence (ɸ) , mean amplitude (V mean) , pulse repetition rate (PRR) , and phase span (ɸ span). These quantities are extracted from a phase-resolved partial discharge (PRPD) pattern using a pulse detection algorithm. Later, these characteristics are analyzed in correlation with the electrical stress. Various regression models are implemented and compared to find the best fit model that represents trending attributes of major PD characteristics. The presented study can be used as an effective process to analyze the measured PD data for evaluation of the insulation condition in the power components. [ABSTRACT FROM AUTHOR]

ABSTRACT—Partial discharge (PD) diagnostic is an effective tool for condition monitoring of the high-voltage equipment that provides an updated status of the dielectric insulation of the components. Reliability of the diagnostics depends on the quality of the PD measurement techniques and the processing of the measured PD data. The online measured data suffer from various inaccuracies caused by external noise from various sources such as power electronic equipment, radio broadband signals and wireless communication, etc. Therefore, extraction of useful data from the on-site measurements is still a challenge. This article presents a discrete wavelet transform (DWT)-based adaptive denoising algorithm and evaluates its performance. Various decisive steps in applying DWT-based denoising on any signal, including selection of mother wavelet, number of levels in multiresolution decomposition and criteria for reconstruction of the denoised signals are taken by the proposed algorithm and vary from one signal to another without a human intervention. Hence, the proposed technique is adaptive. The proposed solution can enhance the accuracy of the PD diagnostic for HV power components. [ABSTRACT FROM AUTHOR]

Insulated power cables are becoming increasingly popular in today’s developing distribution and transportion networks. However, due to aging, deterioration, and various operational and environmental stresses, insulation defects may appear and so the cable needs to be monitored in a timely manner to avoid unexpected failures. Many of these defects are responsible for partial discharge (PD) activity. The localization of the sources of these discharges is a highly decisive facet in the condition-based monitoring of power cables. The techniques for the localization of single-PD defects in insulated power cables are well presented in the current bibliography. However, when several simultaneous PD sources are active, the localization of the sources becomes quite complex. This paper develops an efficient technique for the separation and localization of multiple PD sources in a medium voltage cable. The experimental results are obtained with single-end-based measurements using a high-frequency current transformer in a laboratory environment. The data processing based on the spectral characteristics of the signals is carried out by using the power ratios technique in order to determine the presence of different types of PD. Once the signals are separated, the PD sources can be localized with an individualized analysis of each source through time-domain reflectometry. The proposed methodology can be very valuable to improve the location diagnostic capability of the condition-based monitoring solutions, especially for underground cables. [ABSTRACT FROM AUTHOR]

• Impact of electrical stresses on PD activity in the insulation defects. • Evaluation of severity of insulation defects through PD characteristic features. • Trend analysis of PD features in insulation defects by increasing electrical stresses. • Development of Tobit regression to identify the trends and to predict the PD behavior. Assessments of aging and insulation degradation in power components are important to observe and track their condition during operation. Partial discharge (PD) diagnostics is an efficient method for health estimation of the components' insulation. PD is initiated when the dielectric strength of localized insulation part is decreased. The intensity of PD increases with time, which may lead to insulation failure. This paper investigates the influence of the electrical stresses on the behavior of PD activity in medium voltage (MV) cable containing insulation defects. For this purpose, insulation defects such as internal, surface, and corona are developed in the MV cable environment under laboratory conditions. PD behavior is studied in these defects at gradually increased voltage levels by observing different PD characteristic features including PD inception voltage (PDIV), pulse repetition rate, accumulated apparent charge, average discharge current, discharge power, and quadratic rate. The Tobit regression model is developed for these progressing defects to identify the trends and to predict the behavior based on PD characteristic features. The presented work proposes a framework for the evaluation of the progression of insulation degradation due to increased electrical stress. The study is carried out on XLPE cables, however, the developed approach can be equally implemented on other types of dielectrics and components. [ABSTRACT FROM AUTHOR]

In this paper, a series of investigations on sensitivity and bandwidth for four types of Rogowski coil (RC) sensors was demonstrated. The proposed RC sensor design using acrylonitrile butadiene styrene material carries the advantages, such as lighter weight, robust, and higher temperature resistance. The prototype development first was carried out with the assistance of Solidwork 3D computer aided design software and MakerBot 2X 3D printer. Subsequently, the sensors were modeled and simulated using electromagnetic transient program-alternative transient program software environment based on the lumped parameter identification. A single-end measuring technique was used to locate the PD signal on the three-phase medium voltage underground cross-link polyethylene insulated power cable with a 240-mm2 nominal area copper conductor. In order to verify the results achieved from the simulation, an experiment was carried out. This experiment was repeated concurrently for each design of the RC sensors. In order to achieve the best PD detection, the precise selection for the best sensor is paramount. In this case, the results indicated that certain geometrical shape performed better with regard to the detection of the PD signal. [ABSTRACT FROM PUBLISHER]

High energy arc faults in medium-voltage (MV) switchgear are serious hazards to personnel or equipment, and may cause process interruptions. Most of the electrical faults leading to arc are developed slowly, e.g., due to insulation degradation or bad connection. In this paper, the detection of partial discharges (PDs) and low energy arcing between loose contacts has been proposed for online monitoring of MV switchgear. The PD measurements in a switchgear panel and arcing measurements across a 0.2-mm sphere-to-rod gap have been carried out. Measured signals are captured by a differential electric field sensor ( $D$ -dot sensor) and recorded by a high-frequency oscilloscope. In general, online measured signals are suppressed by high-frequency noise, and therefore, de-noising of measurements is of paramount importance to get reliable information about a fault. An implementation of discrete wavelet transform, to de-noise the measured signals, has been proposed in this paper. Comparison with a well-known infinite impulse response filtering technique has been made. Time and frequency domain comparisons between original and de-noised signals reveal the significance of this technique for arc fault prediction in MV switchgear. A layout for the integration of online monitoring to central control is also presented. [ABSTRACT FROM PUBLISHER]

The major types of slowly developing faults, which can lead to arc faults in switchgear and controlgear, such as partial discharge, arcing, and heating due to poor connections, can now be successfully detected and monitored. In parts I and II of this paper series, a detailed review of the immediate causes of arc faults, along with an overview of preignition and postignition methods for its mitigation, was presented. Various hybrid nonintrusive sensors were developed in the laboratory to implement preignition detection techniques. The major types of slowly developing electrical faults were created in the laboratory, and the sensors were employed to evaluate their performance along with an effective signal processing technique. Part III of the work is based on the successful performance of the sensors outside of laboratory conditions. Hybrid sensors have been installed in a real-world application, i.e., switchgear located in substations. This paper presents interesting results about this practical application and includes valuable discussion on the performance evaluation of different sensors, which further justifies the usefulness of the new sensors for online condition monitoring of switchgear, controlgear, and cable termination boxes. The implementation of this technology in industry may provide promising results in avoiding major accidents such as arc-flash in the switchgear and controlgear. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) diagnostic is considered as the main concern while making condition assessment plan for medium voltage assets. PD detection and localization in multi-section (straight and branched power lines) MV network is difficult by using the conventional Time Domain Reflectometry and Time Difference of Arrival methods. It is due to interconnected cables of different lengths and properties which make the interpretation of PD signals quite complex as compared to single cable routes. This paper presents an online technique of PD localization in MV cable network. PD activity emits current pulses propagating away from the PD site. Polarity of the detected PD pulses with reference to polarity of the supply voltage determines the direction of arrival of these pulses. Comparison of the polarity of PD pulses identifies the faulty section of the overhead covered conductor line as well as the cable network. A detailed discussion has been presented to address the practical issues of sensor implementation and polarity comparison in order to ensure the accuracy of polarity based direction of arrival (DOA) assessment during field application. Evaluation of DOA is based on directionally calibrated sensors. Allocated induction sensors are employed along the feeder for integrated implementation of proposed technique in accordance with the distributed agent for improving the network reliability. [ABSTRACT FROM AUTHOR]

Highlights: [•] Laboratory construction and characteristics depending on geometry of the Rogowski coil are discussed in detail. [•] Experimental analysis of various geometrical designs of Rogowski coil for high frequency current pulse measurement. [•] Quantified comparison of effects on coil’s behavior due to variation in its geometry. [•] Recommendations for selecting optimal design of Rogowski coil. [Copyright &y& Elsevier]

Already installed cables are aging and the cable network is growing rapidly. Improved condition monitoring methods are required for greater visibility of insulation defects in the cable networks. One of the critical challenges for continuous monitoring is the large amount of partial discharge (PD) data that poses constraints on the diagnostic capabilities. This paper presents the performance comparison of two data acquisition techniques based on phase resolved partial discharge (PRPD) and pulse acquisition (PA). The major contribution of this work is to provide an in-depth understanding of these techniques considering the perspective of randomness of the PD mechanism and improvements in the reliability of diagnostics. Experimental study is performed on the medium voltage (MV) cables in the laboratory environment. It has been observed that PRPD based acquisition not only requires a significantly larger amount of data but is also susceptible to losing the important information especially when multiple PD sources are being investigated. On the other hand, the PA technique presents improved performance for PD diagnosis. Furthermore, the use of the PA technique enables the efficient practical implementation of the continuous PD monitoring by reducing the amount of data that is acquired by extracting useful signals and discarding the silent data intervals. [ABSTRACT FROM AUTHOR]

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. • Identification of trends and patterns from partial discharge events in power cables at various voltage levels. • Segregation of events into significant (partial discharge) and stationary events (noise in measurement). • Characterization of the significant events in terms of time of occurrence, duration of event, angle at which it occurred, and change in magnitude. • Trends of significant events as in frequency of occurrences, number of events and location. • Rate of change of significant partial discharge events with respect to duration of occurrences [ABSTRACT FROM AUTHOR]