A versatile solution for continuous on-line PD monitoring

On-Line Continuous Partial Discharge (PD) measurements of medium voltage substations are an excellent way to determine the overall health of the equipment. Partial discharge measurements can provide maintenance alerts to allow scheduling of equipment outages based on actual condition data as opposed to scheduling based on time intervals. PD measurements provide information about the insulation system that is impossible to extract with other methods. Remote monitoring adds additional value to continuous monitoring by relieving customers of the burden of data analysis, readily involving remote experts. This paper discusses the effectiveness of PD measurements using multiple sensors. Multiple sensors provide additional noise reduction and the ability to localize PD activity for measurements made in higher frequency bands. The importance of continuous PD monitoring vs. periodic walk in PD measurements for switchgear is also discussed. PD activity in switchgear can be unstable and dependent on ambient conditions. Negative periodic PD tests in switchgear can result in a false sense of security. Case studies from field experience are presented to support the discussions.

This paper introduces a computerized online PD (Partial Discharge) monitoring and diagnostic system for power transformers, which has been installed in a 500 kV substation in China. It consists of wide-band active transducers and DAU (Data Acquisition Unit) with modularized and exchangeable components. This system has been developed to monitor multiple parameters of multiple power transformers, which is based on COM (Component Object Model). In addition, the system can also be used to monitor other power equipment. Some results of on-line monitoring are discussed.

The assessment of the insulation condition of high-voltage power transmission networks using a non-invasive method of online partial discharge (PD) monitoring is currently a common practice in maintenance programs for elements of the distribution and transmission networks. The joint-stock company „Elektromreža Srbije“ Belgrade (EMS AD) manages a large number of power equipment (EES), on which various partial discharge monitoring strategies can be applied to control the insulation condition. One of the goals of EMS AD is to implement a real-time monitoring system aimed at optimizing the maintenance process and conducting diagnostics for the early detection of insulation defects and predicting failures in cable lines. The paper describes the activities related to the implementation of an online monitoring system for partial discharge detection, which involves the installation of permanent high-frequency sensors at strategic locations to diagnose the insulation condition of cable lines. Additionally, different levels of diagnostics are presented through the use of a software tool for automatically eliminating partial discharges that do not originate from insulation defects, as well as a tool for localizing partial discharges along the length of the cable line.

Partial discharge (PD) monitoring applications enable the performance of appropriate diagnosis regarding the insulation condition of high-voltage (HV) electrical grids. During the last decade on-line PD monitoring systems have been increasingly implemented by utilities and large electricity consumers in HV installations. Therefore, the evaluation of their performance is interesting in order to check whether they are generally effective with respect to their functionalities. For the characterisation of the PD monitoring instruments and of the requirements of acquisition time (number of cycles per second), the performance of laboratory tests with real insulation defects is required. As these are monitoring tests, they entail a long time (at least one day), and during this time the monitored insulation defects must behave in a stable manner. The main scope of the study presented is to design, manufacture and characterise the behaviour of three test cells, each integrating a characteristic insulation defect, with the aim of using them in laboratory monitoring tests lasting at least one day. The considered insulation defects are as follows: an internal cavity in a solid dielectric, corona effect and a surface defect. The measurements carried out with the designed test cells have shown that they are suitable for their implementation in PD monitoring tests of long duration.

Partial discharge (PD) based condition monitoring has been widely applied to power cables. However, difficulties in interpretation of measurement results (location and criticality) remain to be tackled. This paper aims to develop further knowledge in PD signal propagation in power cables and attenuation by the PD monitoring system devices to address the localization and criticality issues. As on-line or in-service PD monitoring sensors commonly comprise of a high frequency current transformer (HFCT) and a high-pass filter, the characteristics of detected PD pulses depend on the attenuation of the cable, the HFCT used and the filter applied. Simulation of pulse propagation in a cable and PD monitoring system are performed, based on analyses in the frequency domain using the concept of transfer functions. Results have been verified by laboratory experiments and using on-site PD measurements. The knowledge gained from the research on the change in pulse characteristics propagating in a cable and through a PD detection system can be very useful to PD denoising and for development of a PD localization technique.

Partial Discharge (PD) measurement is an effective method to detect degradation processes in medium and high voltage equipment. As an example, after-laying PD test have become mandatory in many countries as a commissioning test for high voltage cable systems. This type of test can assess the presence of defects just after installation, but thermal cycling, electrical and thermal stress as well as contamination can lead to the onset of defects at a later time. To cope with defects arising during operation, the key is PD monitoring (offline tests are often too costly in terms of equipment, personnel and loss of revenues). This paper presents the application a of permanent PD monitoring system based on a Ultra-Wide band (UWB) detector to high voltage transition joints linking old fluid-filled cables with new XLPE cable lines. These cable accessories are highly critical because of the complexity of their insulation system and the fact they are realized on field (uncontrolled environment). The innovative monitoring scheme fully exploits the benefits coming from using a UWB detector, i.e., selective tracking of PD based on PD pulse characteristics. This approach enables to trend various PD sources separately, highlighting those that are associated with degradation phenomena within the insulation system. This approach will be unraveled and demonstrated by monitoring data coming from two cable lines.

Partial discharge (PD) online monitoring is an effective tool of inspecting insulation defects and identifying potential faults in power transformers. Ultra-high-frequency (UHF) approaches have caught increasing attention recently and been considered as a promising technology for online monitoring PD signals. The size of a UHF sensor for PD online monitoring of transformer is a critical factor for practical installation inside transformer. This communication presents a compact fourth order UHF Hilbert fractal antenna with desired performance and suitable size for easy installation. Actual PD experiments were carried out for four typical artificial insulation defect models while the antenna was used for PD measurements. The experimental results show that the proposed Hilbert fractal antenna is suitable and effective for UHF online monitoring of PDs in transformers.

Localizing faults in underground cables is a two-dimensional inverse problem, including the depth as the vertical dimension and the horizontal distance from the supply point. In this paper, a new approach based on magnetic field sensing is developed to accurately locate faults in underground cables without physically accessing them. Three types of fault are addressed, line-to-ground fault (LGF), leakage current fault (LCF), and line-to-line fault (LLF). Based on magnetic field sensing, the cable is first localized. Afterwards, the depth is calculated using the Quotient method and finally, the horizontal distance is determined using Kirchhoff’s law (KVL). The simulation results show average errors of 5.25%, 4.77%, and 3.53% for LGF, LCF, and LLF. respectively, while the experimental results yield errors of 20% and 29% for LGF and LLF. These findings highlight the reliability of the proposed approach. Additionally, since the method requires only a single magnetic field sensing device with minimal computational effort, it offers a practical and cost-effective solution for the location of underground cable faults.

Online monitoring of partial discharges (PD) can reduce the risk of catastrophic failure of power apparatus. Acoustic emission technique is advantageous for online PD measurement. PDs are classified according to the origin of discharges and their effects on insulation deterioration are also different. Acoustic emission (AE) signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for analysis. PDAE signal propagates from source to sensor through oil and pressboard insulation. This paper discusses the effects of different thicknesses of pressboard insulation barrier on the propagation path of partial discharge acoustic emission signal. PD may occur at surface of insulation having different thickness at different voltages. This paper also discusses the effect of insulation thickness on surface discharge. The behavior of PDAE signal at different voltage level is also discussed. The AE signals are analyzed using FFT and DWT. The parameters calculated are frequency at peak magnitude & median frequency from FFT data and percentage signal energy in different frequency bands from DWT data. Effect of applied voltage beyond PD inception voltage is also examined. Acoustic PD magnitude (mV) and electrical PD magnitude (pC) relation for different electrode system is investigated.

We constructed an on-line partial discharge (PD) monitoring system (PDOM) with a CT sensor, an analogue-digital converter, and a tablet PC. A sampling frequency for data acquisition is 100 MHz, and we exchange on-site PD data through a cloud system. We successfully measured PDs in the early stage of insulation deterioration of a cross-linked polyethylene (XLPE) cable in a field site. Additionally, following PD detection by using a PDOM, we can locate a PD position by using a PD locator (PDL) system. By locating a PD, we can estimate the actual PD magnitude considering attenuation factor of a high frequency pulse. We show how the PDL system works on a XLPE cable network with time synchronization between two positions by using an injection current pulse. The locating accuracy of the PDL system is evaluated.

For medium voltage (MV) power cables with voltages between 5 and 35 kV that provide power to emergency and safety support systems in nuclear power plants (NPPs), degradation and failure of cables due to water exposure has occurred. Systematic studies of current NPP MV cable systems are being carried out to determine and characterize cable-aging mechanisms and provide greater accuracy to models being developed to predict MV cable field performance to support existing cable aging management and monitoring programs. To validate models based on representative laboratory specimens, samples from harvested MV cable systems are being subjected to accelerated aging and degradation from humid conditions and submergence. Degradation will be characterized via partial discharge and voltage endurance testing of the cable and induced water tree growth in insulation. The technical approach to be used for the testing harvested MV cable samples is presented.

Insulation breakdown is one of the common faults in the operation of high voltage switchgear. The most effective way to prevent insulation breakdown is to detect the partial discharge(PD) phenomenon of high voltage switchgear in operation timely and accurately. The ultrasonic method and the UHF method are so expensive that are only suitable for regular inspection. To this end, this paper presents and designs an on-line monitoring device for PD of the switchgear cabinet based on the transient earth voltage and the spectrum analysis. This device uses the high-frequency current transformer and capacitance sensor where the three-phase electrostatic display is to obtain the pulse current when discharge occurs from the switchgear to the ground. After high-pass filtering, this device catches frequency signals with the help of FPGA and AD9236 which is a high-speed acquisition chip. Using the microprocessor, this design obtains the spectrogram of discharge pulse. With the help of the measurement of high-frequency signal in the spectrogram, this device determines whether PD occurs in the switchboard and the PD levels. Having tested, the device can qualitatively monitor the partial discharge condition of switchgear, and meet the requirements of PD's online monitoring. Because the on-line monitoring device for PD does not require expensive sensors, it's easy to promote the application.

The partial discharge (PD) is the most common fault of transformers, which is the main factor affecting the stable operation of transformers. Therefore, the PD should be monitored and identified timely to improve the reliability of the transformers. In this paper, a transformer PD pattern recognition algorithm based on the gray-level co-occurrence matrix of optimal parameters and support vector machine (GLCMOP-SVM) is proposed. Firstly, the GLCM of optimal parameters (GLCMOP) is proposed to be determined by calculating the proportion of the off-diagonal elements (PODE) in GLCM. The GLCMOP has the advantage of avoiding the subjectivity of parameter selection and simplifying the calculation process. Then, the phase-resolved partial discharge (PRPD) maps are used as the PD samples and are converted into the GLCMOP to extract the PD features. Moreover, the feature space of the GLCMOP is dimensionally reduced by screening out the features with high distinguishability, which can improve the generalization ability and recognition speed of the classifier. Finally, the SVM classifier is trained to sort the PD samples and recognize the PD types, which include the tip discharge, surface discharge, and air discharge PD types. Lab tests are performed to verify the accuracy and validity of the proposed methodology. Compared with the traditional algorithms based on GLCM, XGBoost (eXtreme Gradient Boosting) and artificial neural network (ANN), the performance of GLCMOP-SVM is better. The GLCMOP-SVM has less memory consumption and faster recognition speed, so it is very suitable for the online and real-time monitoring of PD occurred in the transformers.

For many years identification of incipient Partial Discharge (PD) faults in power cables has been made through off-line investigation techniques. The periodic monitoring of power cables resulted in unexpected failures, with consequent financial penalties for the utilities. More recently, in an effort to allow continuous asset management of the medium voltage cable network to be carried out, on-line monitoring systems are being installed with the aim of reducing unexpected failures. This paper presents work on the analysis and handling of data acquired from an on-line system.

The on-line monitoring of partial discharge on generators is more and more widely used to estimate the insulation condition of generator stator windings. In this paper a new detector for on-line monitoring of partial discharges of generators was introduced. The measurement of partial discharges was carried out on some generator model bars in a laboratory using the new detector. Features of different types of PD were analyzed using the spectrums of Hq(/spl phi/), Hn(/spl phi/) and Hn(q). Some primary results from field test are reported for a detector installed on a turbine generator in a power plant located in Shanxi Province of China.