Feasibility study on application of microwave radiometry to monitor contamination level on insulator materials

This paper introduces a novel method for monitoring contamination levels on high voltage insulators based on microwave radiometry. Present contamination monitoring solutions for high voltage insulators are only effective in predicting flashover risk when the contamination layer has been wetted by rain, fog or condensation. The challenge comes where the pollution occurs during a dry period prior to a weather change. Under these conditions, flashover can often occur within a short time period after wetting and is not predicted by measurements taken in the dry period. The microwave radiometer system described in this paper measures energy emitted from the contamination layer and could provide a safe, reliable, contactless monitoring method that is effective under dry conditions. The relationship between equivalent salt deposit density and radiometer output is described using a theoretical model and experimentally verified using a specially designed X-band radiometer. Results demonstrate that the output from the radiometer is able to clearly distinguish between different levels of contamination on insulator materials under dry conditions. This novel contamination monitoring method could potentially provide advance warning of the future failure of wet insulators in climates where insulators can experience dry conditions for extended periods

Prediction of The High Voltage Insulators Service Life Based on The Effective Values of Leakage Currents

The insulation condition of overhead lines is one of the main factors affecting reliability of overhead power transmission lines. It is known that the process of insulation lapping or rupture is mainly affected by environmental conditions and the degree of pollution of the insulators surface. This paper substantiates the possibility of using the leakage current values of insulators for monitoring the state of insulation and predicting its resource. The results of experimental studies of leakage currents of high-voltage insulators depending on their service life are given, on the basis of which forecasting the possible resource of insulators is carried out. The results obtained can be used to develop more effective diagnostics for detecting insulator failures at an early stage to take appropriate measures to coordinate the insulation

An Underappreciated Radiation Hazard from High Voltage Electrodes in Vacuum

The use of high voltage (HV) electrodes in vacuum is commonplace in physics laboratories. In such systems, it has long been known that electron emission from an HV cathode can lead to bremsstrahlung X-rays; indeed, this is the basic principle behind the operation of standard X-ray sources. However, in laboratory setups where X-ray production is not the goal and no electron source is deliberately introduced, field-emitted electrons accelerated by HV can produce X-rays as an unintended hazardous byproduct. Both the level of hazard and the safe operating regimes for HV vacuum electrode systems are not widely appreciated, at least in university laboratories. A reinforced awareness of the radiation hazards associated with vacuum HV setups would be beneficial. We present a case study of a HV vacuum electrode device operated in a university atomic physics laboratory. We describe the characterisation of the observed X-ray radiation, its relation to the observed leakage current in the device, the steps taken to contain and mitigate the radiation hazard, and suggest safety guidelines.Comment: Submitted to Health Physic

Inception 1D-convolutional neural network for accurate prediction of electrical insulator leakage current from environmental data during its normal operation using long-term recording

[EN] Contamination flashover remains one of the biggest challenges for power grid designers and maintenance engineers. Insulator leakage current contains relevant information about their state so that continuous monitoring is considered the most effective way to prevent contamination flashover. In this work, we attempted to accurately predict insulator leakage current in real time during normal operations based on environmental data using long-term recordings. We first confirmed that the history of environmental data also contained relevant information to predict leakage current by conditional Granger analysis and determined that 20 was the optimal previous samples number for this purpose. We then compared the performance of typical regression models and convolutional neural network (CNN), when using both current and the last 21 samples as input features. We confirmed that the model with the last 21 samples might perform significantly better. Input features pre-processing by cascaded inception architecture was fundamental to capture the complex dynamic interaction between environmental data and leakage current and significantly improved the model performance. CNN based on inception architecture performed much better, achieving an average R2 of 0.94 ±0.03. The proposed model could be used to predict leakage current in both porcelain insulators with or without coatings and silicone composite insulators. Our results pave the way for creating an on-line pre-warning system adapted to individual installations, can anticipate the negative consequences of weather and/or pollution deposits and is useful for designing a strategic high-voltage electrical insulator preventive maintenance plan for preventing contamination flashover and thus increase power grid reliability and resilience.This work was supported by the Spanish Ministry of Economy and Competitiveness, Spain, the European Regional Development Fund (MCIU/AEI/FEDER, UE RTI2018-094449-A-I00-AR) .Bueno Barrachina, JM.; Ye Lin, Y.; Nieto Del-Amor, F.; Fuster Roig, VL. (2023). Inception 1D-convolutional neural network for accurate prediction of electrical insulator leakage current from environmental data during its normal operation using long-term recording. Engineering Applications of Artificial Intelligence. 119. https://doi.org/10.1016/j.engappai.2022.10579911

Sensoring Leakage Current to Predict Pollution Levels to Improve Transmission Line Model via ANN

Pollution insulator is a serious threat to the safety operations of electric power systems. Leakage current detection is widely employed in transmission line insulators to assess pollution levels. This paper presents the prediction of pollution levels on insulators based on simulated leakage current and voltage in a transmission tower.The simulation parameters are based on improved transmission line model with leakage current resistance insertion between buses. Artificial neural network (ANN) is employed to predict the level of pollution with different locations of simulated leakage current and voltage between two buses. With a sufficient number of training, the test results showed a significant potential for pollution level prediction with more than 95% Correct Classification Rate (CCR) and output of the ANN showed high agreement with Simulink results

Computerised measurements and condition monitoring for polymeric insulators at a large outdoor test station

Il lavoro è stato sviluppato con l’obbiettivo di effettuare delle misure su correnti di lieve entità e per il rilevamento di scariche parziali sugli isolatori. Lo studio ha dapprima coinvolto l’apprendimento teorico dello stato dell’arte delle ormai consolidate tecnologie per le strutture degli isolatori. Quindi, sono state prese in considerazione le problematiche dovute alla presenza di condizioni ambientali sfavorevoli. Lo studio è poi proseguito con la valutazione del parametro elettrico utile a identificare lo stato di salute degli isolatori: la corrente di dispersione, per la quale sono stati approfonditi diversi trasduttori. Il lavoro, inizialmente analizzato in un contesto teorico, è stato poi applicato in un test sperimentale nel laboratorio di alte tensioni dell’Università di Cardiff. È stata effettuata un’analisi di caratterizzazione dei trasduttori, dei quali due ne sono stati utilizzati in seguito per l’analisi della corrente di dispersione su un particolare isolatore polimerico. L’intero sistema di misurazione a partire dal generatore, dal filtro passa-basso, dal trasformatore elevatore, dal divisore di tensione fino all’isolatore polimerico è stato analizzato per avere a disposizione un sistema di misura al quanto più accurato. Sono stati effettuati due test: uno considerando l’isolatore asciutto e l’altro bagnando le superfici dell’isolatore per emulare una condizione ambientale sfavorevole. I risultati sono quindi stati elaborati con il software Matlab. Lo scopo è stato quello di studiare l’affidabilità dei trasduttori impiegati. Per concludere, sono stati analizzati vari sistemi per l’accesso da remoto dei risultati ottenuti e un piccolo esperimento a riguardo è stato effettuato.In the present work, a measuring system able to detect a small current magnitude and partial discharges activities on polymeric insulators has been studied. Starting from a state of the art of the nowadays steady technologies of insulators design, the study has been moved to the relevant problems caused by aging effects. Hence, considering the issues that could involve outdoor insulators, an important electrical parameter has been taken into account: the leakage current. To detect this kind of current, many transducers have been analysed. From the theory, the work has moved to an experimental test in the high voltage laboratory of Cardiff University. A characterization of the transducers has been carried out and two of them have been tested to detect the leakage current in a textured polymeric insulator. All the measurement system from the generator to the low-pass filter, the step-up transformer, the voltage divider and the textured polymeric insulator has been analysed to be sure that the whole system can correctly work. The two insulator tests, the dry and the wet pollution test, have been carried out and the results compared and so, analysed with Matlab. The aim was to study the transducer reliabilities. Finally, simple systems for the remote access of data have been studied and a little experimental test has been carried out

MCHO – A new indicator for insulation conditions in transmission lines

AbstractConventionally monitoring operating conditions of a power transmission line is accomplished by periodic inspections along this line. This monitoring allows corrective maintenance by finding faults during the inspection. But in more efficient maintenance, predictive techniques that are characterized by real-time monitoring should be employed. Such predictive techniques allow for verifying the working status of the line by using normal working models to detect faults and fault models for diagnosis. This paper presents a study that used a mathematical model appropriate for application to predictive maintenance of transmission line segments at low cost, without the need for sensors distributed along the line, and presenting a new indicator of transmission line operation conditions. By tracking the leakage current of transmission lines, this model allows for estimating the current line insulation status. Once the current line insulation status is known, it is possible to compare it against other future status and verify the progress of the insulation conditions of that line. The model uses a new indicator, called MCHO, which can detect and diagnose both normal and abnormal operating conditions of a power transmission line. This new indicator is the capacitance of the harmonic frequencies of the transmission line leakage current. The model was validated through measurements obtained on a stretch of transmission line

A wireless system for monitoring leakage current in electrical substation equipment

In this paper, the design and the development of a remote system for continuous monitoring of leakage currents and ground currents in high voltage electrical substations are proposed. Based on wireless local area network technology, the system can be used to monitor continuously a variety of plants within the substation and has low power consumption with inbuilt overvoltage protection. It consists of a transmitter module equipped with a data acquisition (DAQ) system connected to leakage current and voltage sensors, and a receiver module connected to a remote controller for data processing and storage. The principle of operation and the characteristics of the various components of the system are described. Validation tests have been used to verify its performance in three different test situations: A) laboratory monitoring of the leakage current and voltage of a distribution surge arrester; B) laboratory measurement of the leakage current of an outdoor insulator; and C) field monitoring of the earth current and potential rise of high-voltage tower. The measured results are in close agreement with those recorded directly through a DAQ card with fiber-optic and coaxial cable connected systems. Data processing is carried out at the receiving end so that the monitored parameter is displayed continuously or at specified time intervals. The operation of the system has been tested and proved resilient under high-frequency interference signals such as those generated by corona and surface discharges