Accurate location of the origins of partial discharges in power cable systems, based on arrival times, is imperative for the identification and assessment of defects. This paper evaluates different time-of-arrival algorithms in order to determine which method yields most accurate location under different circumstances. These methods are based on trigger level, Akaike Information Criterion, energy criterion, Gabor's signal centroid and phase in frequency domain. Several criteria are defined by which the algorithms are evaluated. These criteria include the sensitivity to noise, pulse shape and effect of load impedance. The sensitivity of the methods upon varying these quantities is evaluated analytically and by means of simulations. Further, the methods are tested on a medium-voltage cable system by injecting PD pulses in a cable with one joint. Each algorithm is applied to the measured pulses and the resulting location is compared with the known joint location. From the results the energy criterion method and the phase method show the best performance.

/pdf/accurate-estimation-of-the-time-of-arrival-of-partial-2l5lg7kpe4.pdf

Accurate estimation of the time-of-arrival of partial discharge pulses in cable systems in service

Partial discharge (PD) diagnostics is a proven method to assess the condition of underground power cables. PDs are symptomatic for a defect (weak spot) that may evolve into a complete breakdown. A PD induces a small pulse in the conductor(s) and earth screen that propagates through the cable in both directions. In previous research an online PD detection and location system was developed for medium-voltage cables. This system is currently introduced by utilities on an increasingly large scale. This thesis deals with several new challenges that are related to the integration of online PD monitoring in different medium-voltage power cable network configurations. A transmission line model of the power cable is required to enable optimal PD detection. A three-core power cable with common earth screen has multiple coupled propagation modes. The propagation modes are decoupled into a modal solution. A practical method to measure and analyze the cable parameters is developed and validated by measurements on a cable sample. Detailed prediction of multiple reflections was achieved, including the mixing of propagation modes having distinct propagation velocities, validating both the model and the measurement method for three-core cables with common earth screen. The semiconducting layers in a cable with cross-linked polyethylene (XLPE) insulation have a significant influence on the transmission line parameters. Unfortunately, the dielectric properties of these layers are usually unknown and can differ between similar cable types. It is shown that nonetheless the characteristic impedance and propagation velocity of single-core and three-core XLPE cables can be calculated using information available from the cable specifications. The calculated values are validated using pulse response measurements on several cable samples. The accuracy of the calculated characteristic impedance and propagation velocity is 5–10%, which is sufficient for estimating PD pulse shape and amplitude in a cable circuit. The online PD monitoring system was initially developed to be installed on a single cable connection between two consecutive ring-main-units (RMUs). It is more efficient to monitor two or more consecutive cables, with one or more RMUs or substations in between, using a single monitoring system. Models for RMUs and substations are proposed and verified by measurements. The influence of RMUs and substations along the cable under test on the PD detection sensitivity and location accuracy is studied using these models and measurements. The influence of a compact RMU with two connected cables is neglectable if the total cable length is longer than approximately 1km. The longer the total cable length, the smaller the influence of an RMU along the cable under test. An RMU or substation along the cable under test with more than two connected cables introduces a significant signal loss, decreasing the detection sensitivity significantly. The higher the number of connected cables, the higher the signal loss. In the equipment found in some substations and RMUs it is not possible to install a PD measurement unit at a desired location. The models and measurements are used to study the feasibility of a single-sided PD measurement, including PD location, with the problematic RMU/substation at the far end. The study shows that a major part of an incoming pulse reflects on a large RMU/substation with many connected cables. This reflection enables a single-sided PD measurement from the other cable end. A single-sided measurement has the disadvantage that the maximum cable length that can be monitored is halved and that it is sensitive to reflections on joints in the cable under test and other connected cables. Accurate location of PDs in cables, based on arrival times, is imperative for the identification and assessment of defects. Five algorithms that determine the time-of-arrival of pulses are evaluated to investigate which method yields the most accurate location under different circumstances. The methods are evaluated analytically, by simulations, and by measurements on a cable system. From the results the energy criterion method and the phase method show the best performance. The energy criterion is a robust method that achieves location accuracy of 0.5% of the cable length or better. The phase method has a good performance only if the phase shift introduced at the transmission from the cable under test to the RMU is known accurately. For maximum detection sensitivity the PD monitoring system uses matched filters. These filters are constructed using predicted PD waveforms. These predictions are based on a series of online system identification measurements and a standard cable model. Due to signal distortions that are not taken in account in the model, e.g. an RMU along the cable under test, the predictions can be inaccurate, resulting in a sub-optimal PD detection. An automated procedure that creates new signal templates, based on measured PD signals, is proposed and tested on signals measured during online PD measurements on multiple cable systems. The algorithm generated new templates for PD signals and for disturbing pulses. New PD pulse templates for may be used to improve the cable system model. Disturbing pulse templates may be used to improve disturbance rejection by the measurement unit.

/pdf/integration-of-online-partial-discharge-monitoring-and-3hxr32nlgk.pdf

Integration of online partial discharge monitoring and defect location in medium-voltage cable networks

To allow utilities to fulfill self-imposed and regulative performance targets that apply to them, the demand for new tools to help judge the health of modern power distribution networks has increased. The analysis of partial discharge (PD) signals has been identified as a potential diagnostic tool for the condition monitoring of HV plant. In order to investigate the PD activity produced by a range of defects within three-phase paper insulated lead covered (PILC) distribution cable under rated conditions, an experiment has been developed. The experiment incorporates a commercially available on-line PD measurement system employing a high frequency current transformer (HFCT) to record PD data in a manner that is currently in operation in the UK. By replicating field conditions and using realistic hardware to collect experiment data, that any findings or analysis tools developed during this investigation are directly transferable to use in the field. Four defective cable samples, each containing different imperfections that are known to reduce in-service plant life have been fabricated and extensively PD tested. The raw experiment data was processed to produce a dataset containing a range of features from individual PD pulses including time, frequency and time-frequency information. This data was used to optimize and train several support vector machine (SVM) models to perform automated pulse classification. Four SVM models were tested using different combinations of pulse features to identify which characteristics were most effective at transferring source dependent information for classification. The results of the automated algorithm validated the approach returning a classification accuracy of 91.1%.

Autonomous classification of PD sources within three-phase 11 kV PILC cables

The analysis of partial discharge (PD) signals has been identified as a standardized diagnostic tool in monitoring the condition of different electrical apparatus nowadays. In this paper, we propose a novel data-driven approach to detect PD pulses in power cables using one-dimensional convolutional neural networks (CNNs), a successful deep neural network approach. Applying this deep learning method, an end-to-end framework has been proposed considering the propagations of PD signals and noises in power cables. The proposed method uses PD pulses as input, automatically extracts meaningful features for waveforms of PD pulses, and finally detects PD. Most of the existing methods, which use traditional classifiers, such as support vector machines (SVMs) and multi-layer perceptron (MLP) have mainly focused on improving feature representation and extraction manually for this task. However, the proposed CNN-based detection algorithm captures important latent features for waveforms of PD pulses with the help of its automatic feature extraction capability from raw inputs. Our experimental results show that the proposed method is better than conventional SVMs and achieves 97.38% and 93.23% detection accuracies in end-to-end settings based on our theoretical model-generated and empirical real-world PD signals, respectively.

End-to-End Partial Discharge Detection in Power Cables via Time-Domain Convolutional Neural Networks

Partial discharge (PD) detection and location in cable systems is a valuable tool for the estimation of the condition of the system. Accurate localization of the PD origin, based on arrival times, is required for the identification and assessment of the defect. This paper evaluates different time-of-arrival algorithms to determine which method yields most accurate location under different circumstances. These methods are based on trigger level, Akaike Information Criterion (AIC), energy criterion, Gabor's signal centroid and phase in frequency domain. Several criteria are defined by which the algorithms are evaluated. These criteria include the sensitivity to the noise level, the sensitivity to the pulse shape and others. The methods are tested on a medium-voltage cable system by injecting PD pulses in a cable with a joint at a known location. Each algorithm is applied to the measured pulses and the resulting location is compared with the known location. From the result the methods using the energy criterion and the phase are preferred.

/pdf/algorithms-for-arrival-time-estimation-of-partial-discharge-2ie0tvb1k3.pdf

Algorithms for Arrival Time Estimation of Partial Discharge Pulses in Cable Systems

On-line partial discharge (PD) measurements are an efficient method for detecting certain insulation defects of cables. These include defects in cable joints and terminations, and defects due to mechanical impact. Noninvasive, efficient, and widely applicable, portable on-line PD measurement techniques are strongly favored by the electricity industry. Three on-site PD measurements for cables are described in this article to illustrate how the techniques achieve cost-effective insulation diagnosis to protect the main assets.

Yang Qin

Papers

Cost-effective on-line partial discharge of measurements for cables