Transient Earth Voltage Research Articles

Partial discharge detection, diagnosis, and location technology based on a novel transient earth voltage-ultrasonic integrated sensor used for switchgear equipment.

Medium-voltage (MV) switchgear and gas insulated switchgear (GIS) are essential components of power-grid systems. Their safe operation is crucial for the electricity consumption of users. However, insulation faults often occur during the operation of MV switchgear and GIS because of pollution, humidity, heat, mechanical shock, and other factors. Partial discharge (PD) measurements are the most effective indicator to prevent insulation failure. Transient earth voltage (TEV) and ultrasonic methods are the most popular PD measurement methods for switchgear. Currently, these two methods are used widely and independently. In this study, a novel TEV-ultrasonic integrated sensor is proposed based on the independent structure of the TEV and the ultrasonic sensor. The performance parameters of the proposed sensor were tested on test platforms. PD measurement experiments were conducted in a 10kV switchgear and 220kV GIS to analyze the performance of the integrated sensor. The results show that the sensor can simultaneously measure the TEV and ultrasonic signals in the same location. The integrated sensor can realize effective and sensitive detection, precise location, and accurate diagnosis of PD in the MV switchgear and GIS.

Comparative Study on Multiple Methods for Partial Discharge Detection of Gap Defect in Medium Voltage Switchgear

Abstract The medium voltage switchgear is a key equipment in the distribution network of the power system, which directly faces users. Once a fault occurs, it will cause huge economic losses and adverse social impacts. Partial discharge measurement is an important means to ensure the safe operation of switchgear. The physical quantities measured by different partial discharge detection methods are different, so the detection effects by different methods for the same defect are also different. This paper takes the common internal air gap defects of solid insulation in switchgear as the research object, and conducts partial discharge detection tests on real switchgear equipment. At the same time, radio frequency method, ultrasonic method, transient earth voltage (TEV) method, and pulse current method are used to detect and analyze the partial discharge generated by the defect. The results show that the radio frequency method, TEV method, and pulse current method have good detection sensitivity for air gap defects, but the ultrasonic method cannot detect this type of defect. Comparing the amplitudes of the three electrical signals, it can be found that the correlation between the TEV method and the pulse current method is relatively high, while the correlation between the radio frequency method and the two is relatively low. As the applied voltage increases, the amplitude of the radio frequency method changes linearly, which can more sensitively reflect the degree of defect change.

Robust Autonomous Mobile Manipulation for Substation Inspection

Abstract The need for autonomous infrastructure inspections performed by mobile robots is becoming increasingly prevalent, to mitigate human error and inspect critical infrastructure with increased frequency, while reducing costs. Electric distribution substations contain a variety of high-power equipment that may occasionally fail, and we focus on inspecting pothead compartments as a representative test case. Frequent measurements of acoustic and transient earth voltage data can indicate degradation before failures occur. Handheld partial discharge (PD) sensors can gather these types of data. Measurements using PD sensors can be automated using a mobile manipulation platform with a custom end-effector. Accurate mapping, localization, and navigation are required to perform autonomous inspection tasks in indoor environments with unmanned ground vehicles. Computer vision and precise manipulator control are necessary for successful handheld sensor interactions. In this paper, we present and analyze a custom-integrated mobile manipulation system capable of performing these functions, which achieves a tradeoff between the small size needed to navigate through low-clearance areas, and the reach capabilities needed to collect the required measurements from pothead compartments.

Transient Earth Voltage Sensor Measurements as a Nonintrusive Tool for Partial Discharge Analysis in Switchgears

Transient Earth Voltage Sensor Measurements as a Nonintrusive Tool for Partial Discharge Analysis in Switchgears

Perbandingan Sensor TEV Dan Detektor RC Untuk Pengukuran Partial Discharge Pada Peralatan Tegangan Tinggi

Electrical equipment often faces various issues, with insulation problems being a major cause of failure. This article investigates the comparative effectiveness of two Partial Discharge (PD) detection methods: using Transient Earth Voltage (TEV) sensors and Resistor-Capacitor (RC) detectors. The study was conducted on a metal box with a voltage level of 6 kV. Data collected included Background Noise (BGN) and Partial Discharge Inception Voltage (PDIV), processed using Microsoft Excel and OriginPro 9. Results indicate a correlation between higher BGN values on TEV sensors and earlier PDIV occurrence on those sensors. Background noise significantly impacts the PDIV threshold, influencing sensitivity and insulation risk potential. While PDIV provides a threshold guideline, correlation with BGN helps illustrate the background conditions' influence on PD measurement outcomes. The study offers insights into the importance of considering noise in PD measurements and formulates recommendations for practitioners to choose appropriate detection methods based on specific environmental conditions and electrical equipment.

Partial Discharge Detection and Defect Location Method in GIS Cable Terminal

The complex structure of gas-insulated switchgear (GIS) cable terminals leads to serious electric field concentration, which is a frequent fault position of a high-voltage cable system. At present, due to the differences in the frequency bands of sensors, various partial discharge detection technologies have certain differences in their scope of application and anti-interference performance, resulting in a low defect detection rate in GIS cable terminals. In this paper, a comprehensive diagnosis scheme is proposed, which integrates transient earth voltage (TEV), ultra-high frequency (UHF), high frequency (HF), and ultrasonic methods. Two abnormal discharge defects of GIS terminals in two 220 kV substations in Tianjin were tracked and monitored, and the joint diagnosis was carried out using the proposed scheme; the type of discharge defect and the phase sequence of the defect were determined, and the UHV was employed to precisely locate and analyze the defect source. Finally, through the disassembly analysis and electric field simulation of the GIS cable terminal, the accuracy and effectiveness of the discharge detection and location method were verified, providing a typical detection demonstration for the defect diagnosis of a GIS cable terminal.

Reliable risk-level assessment criteria for vacuum circuit breakers in operation based on transient earth voltage measurements

Reliable risk-level assessment criteria for vacuum circuit breakers in operation based on transient earth voltage measurements

Study on the characteristics of the potential rise of shell under VFTO in the GIS pumped storage power station

Compared with the traditional GIS station, complex wiring and operation mode of pumped-storage plant diversity, working condition of frequent transformation, makes the plant to produce very fast transient overvoltage (VFTO) probability increase greatly. VFTO will form a transient coupled to the GIS shell casing transient earth voltage (TEV), and then to station personnel safety and the reliability of the secondary equipment poses a great threat. But at the moment because of the limitation of testing technology such as understanding of the academic study of TEV is lack of system. Based on a typical 500 kV gis pumped-storage power station, this paper established a system equivalent model of GIS, network frame and calculates the amplitude, frequency spectrum characteristic of the TEV and influence on VFTO characteristics, and analyzes the fault location, power supply mode, branch bus, the influence of vertical grounding electrodes on the TEV characteristics, For the characteristics of the TEV rules and parameters. Research on TEV characteristics of GIS of pumped storage power station has important reference value for further perfecting relevant theories.

Detection Technology of UHF IoT Sensing Terminal Device Based on Cloud Edge Cooperation

Abstract The local release detection technology of traditional Internet of Things (IoT) sensing terminal equipment cannot realize the integration of the cloud and IoT edge, resulting in obvious local release detection errors and low technical sensitivity. To this end, a local release detection technology comprising ultra-high frequency (UHF) IoT sensor terminal equipment based on cloud edge collaboration is proposed. The transient earth voltage signal coupling module of the perception layer is used to collect data locally published by the device. This paper uses edge computing to reduce information redundancy. The cloud computing application layer adopts the time difference positioning method to realize the partial discharge detection of the UHF IoT sensor terminal equipment. When an abnormality occurs in the terminal equipment, an alarm is triggered. The experimental results show that the average accuracy of this method in detecting partial discharge is as high as 93.89 %. The detection time of this method is short and its detection time of partial discharge phenomenon is as low as 4 ms. The fitting effect of the proposed method is better in detecting amplitude and discharge and the two have a linear relationship. This method also has higher detection sensitivity, can detect the partial discharge of different types of terminal equipment, and its application effect is good.

Efficient and Low-Cost PD Monitoring and Locating System for MV Switchgears Using TEV Detectors

Identifying the location of partial discharges (PDs) and providing clear information on insulation vulnerabilities in power systems can help utility companies to improve their maintenance efficiency. This paper presents a PD monitoring and locating system for medium-voltage switchgears using a set of transient earth voltage (TEV) detectors. A time-of-flight methodology was used to identify the switchgear affected by PD among a row of switchgears. A time sharing access mechanism, which was implemented by multiple high-frequency surface mounting relays integrated into each TEV detector, was applied to automatically identify the site of PD and minimize the number of expensive high-speed acquisition cards. The operation principle and implementation of the modular system were formulated, and the efficiency of the proposed system in identifying the switchgear with PD among three 10 kV metal-clad switchgears was confirmed experimentally.

Partial discharge monitoring using deep neural networks with acoustic emission

The occurrence of partial discharge (PD) indicates failures in electrical equipment. Depending on the equipment and operating conditions, each type of PD has its own acoustic characteristics and a wide frequency spectrum. To detect PD, electrical equipment is often monitored using various sensors, such as microphones, ultrasonic, and transient-earth voltage, whose signals are then analyzed manually by experts using signal processing techniques. This process requires significant expertise and time, both of which are costly. Advancements in machine learning, aim to address this issue by automatically learning a representation of the signal, minimizing the need for expert analysis. To this end, we propose a deep learning-based solution for the automatic detection of PD using airborne sound emission in the audible to the ultrasonic range. As input to our proposed model, we evaluate common time-frequency representations of the acoustic signal, such as short-time Fourier, continuous wavelet transform and Mel spectrograms. The extracted spectrum from the PD signal pulses is used to train and evaluate the proposed deep neural network models for the detection of different types of PD. Compared to the manual process, the automatic solution is seen as beneficial for maintenance processes and measurement technology.

Classification of abnormal location in medium voltage switchgears using hybrid gravitational search algorithm-artificial intelligence.

In power system networks, automatic fault diagnosis techniques of switchgears with high accuracy and less time consuming are important. In this work, classification of abnormal location in switchgears is proposed using hybrid gravitational search algorithm (GSA)-artificial intelligence (AI) techniques. The measurement data were obtained from ultrasound, transient earth voltage, temperature and sound sensors. The AI classifiers used include artificial neural network (ANN) and support vector machine (SVM). The performance of both classifiers was optimized by an optimization technique, GSA. The advantages of GSA classification on AI in classifying the abnormal location in switchgears are easy implementation, fast convergence and low computational cost. For performance comparison, several well-known metaheuristic techniques were also applied on the AI classifiers. From the comparison between ANN and SVM without optimization by GSA, SVM yields 2% higher accuracy than ANN. However, ANN yields slightly higher accuracy than SVM after combining with GSA, which is in the range of 97%-99% compared to 95%-97% for SVM. On the other hand, GSA-SVM converges faster than GSA-ANN. Overall, it was found that combination of both AI classifiers with GSA yields better results than several well-known metaheuristic techniques.

Coupling Characteristics of Electromagnetic Disturbance of On-Site Electronic Device Power Port in Substations and Its Suppression

The switching operations of circuit breakers and disconnectors in substations can generate very fast transients, including transient earth voltage rise and intense electromagnetic radiation, causing severe disturbance of on-site electronic devices in substations and seriously affecting the development of smart power equipment. The power supply of an on-site electronic device provides a path along which the disturbance couples with the device. In this article, we investigated the coupling mechanism and measures to suppress this disturbance. We found that, for most on-site electronic devices, their power supply includes a power line that connects the exterior and interior of the shielding box, greatly reducing the shielding effectiveness and inducing disturbance from the outside to the inside. This article proposes a shielding–crossing isolation transformer as the power supply of which the primary winding is outside and the secondary winding is inside of the shielding box, without a power line across the shielding box. This arrangement proved to deliver the high performance in terms of eliminating disturbance from the power supply. This article provides an understanding of the mechanism according to which the electromagnetic disturbance couples through the power supply. A method to determine the electromagnetic compatibility of on-site electronic devices in a substation is also proposed.

Defect Localization Inside Simulated MV Switchgear Based on Cumulative Energy Curve Using Transient Earth Voltage Sensors

The partial discharge (PD) leads to catastrophic failure of the medium voltage (MV) switchgear insulation. Determination of the PD source (defect) location in high voltage (HV) equipment is very important in the maintenance procedures and in isolating the root cause of PD generation. In this paper, the transient earth voltage (TEV) detection method was used to acquire defect-initiated PD signals in a simulated MV switchgear model. An array of four TEV sensors were placed on the surface walls outside an MV switchgear tank to acquire the PD signals generated from the known location(s)/coordinates of sharp needle type defect inside the tank. The time difference of arrival (TDOA) between signals that are captured by the TEV sensors array was critically analyzed. Estimating the TDOA between PD signals generated by PD source at a known location with high accuracy is of great importance for accurate defect localization. The cumulative energy method (CEM) is used to estimate the onset time point of each TEV signal. The estimated TDOA by the cumulative energy method is compared with actual and expected TDOA based on known coordinates of PD source and TEV sensors. Experimental data are used as a basis for determining the TEV method accuracy for PD source localization. Experimental results show the average error of time difference is about 1.34 ns, which is equivalent to the propagation distance of 0.4 m.

Design of Insulation Online Monitoring and Anti-Condensation Control System for Distribution Switchgear

The partial discharge and condensation in distribution switchgear seriously affect the insulation state, which can cause insulation failure and lead to the shutdown of electrical equipment. This paper designs and develops a set of insulation online monitoring and anti-condensation control system for distribution switchgear. By comprehensive use of transient earth voltage (TEV) technology and ultrasonic technology for partial discharge detection, temperature and humidity detection, control technology and wireless communication technology, the system realizes the online monitoring of insulation, temperature and humidity in switchgear. In addition, the system can automatically control the heater, fan or other environmental adjustment equipment and reduce the occurrence of condensation in switchgear.

Flexible Sensor Array Based on Transient Earth Voltage for Online Partial Discharge Monitoring of Cable Termination.

Cable termination is a weak point in an underground cable system. The transient earth voltage (TEV) method is an effective and nonintrusive method for estimating the insulation condition of cable termination. However, the practical application of TEV detection is mainly focused on switchgears, generators, and transformers with a flat and conductive shell. A flexible sensor array based on the TEV method is presented for online partial discharge (OLPD) monitoring of the cable termination. Each sensing element is designed with a dual-capacitor structure made of flexible polymer material to obtain better and more stable sensitivity. Based on the electromagnetic (EM) wave propagation theory, the partial discharge (PD) propagation model in the cable termination is built to analyze and verify the rationality and validity of the sensor unit. Some influencing factors are discussed regarding the response characteristics of sensors. Finally, the performance of the sensor array is verified by simulations and experiments. Besides, an OLPD monitoring system is introduced. The monitoring system is composed of the on-site monitoring device and the remote monitoring host. The two parts of the system exchange the data through wireless networks using a wireless communication module. The experiment results show that the monitoring device could supply the PD condition monitoring demand for cable termination.

Review of research on partial discharge detection techniques of high voltage switchgear

Partial discharge inside a high-voltage switchgear can cause serious accidents. Partial discharge detection can reduce the incidence of accidents. This article summarizes the current research status of common high-voltage switchgear partial discharge detection technologies (Transient Earth Voltage or TEV, Utrasonic or AE and Ultra-High Frequency or UHF), introduces the research status of partial discharge model identification and localization of PD source, and finally looks forward to future research directions.

Equivalence analysis of multiple monitoring methods for partial discharge

In order to study the relationship between the amplitude (mV) and the discharge (pC) of a typical fault of a tip discharge in a partial discharge. Therefore, three different groups of tip electrode models (tip-tip, tip-plate, tip-ball) were simulated. The relationship between magnitude and discharge volume and voltage was obtained by using amplitude detection method (Ultra High Frequency Method, Acoustic Emission Method and Transient Earth Voltage method) and Pulse Current Method respectively. Kendall correlation analysis found that the amplitude and the voltage of the AE Method in the three amplitude detection methods are closest to the variation trend of the discharge quantity and the voltage of the Pulse Current Method. Exploring the equivalence between the amplitude and the discharge of the most accurate detection means, the mathematical model with the best fit is the Sum of Sin Functions.

Insulation Condition Monitoring in Distribution Power Grid via IoT-Based Sensing Network

Insulation condition monitoring is essential for the safety of our distribution power grid. However, the traditional monitoring solution is hardly applied due to the concerns that arise from natures of distribution grid, such as complex feeder networks, massive operation site, and high economic benefit. In this paper, a wireless sensing network based on Internet of things (IoT) technology is demonstrated for insulation condition perception. First of all, the general framework of the wireless sensing network is designed with considerations on extendibility and accessibility. Next, it goes into detail about the technical requirements of the essential units of the sensing network including sensor node, power management, and data communication. With this concept, two practical cases of IoT-based partial discharge sensing networks realized on the switchgear cabinet and power cable are presented with details involving the design of transient earth voltage and high frequency current sensor nodes, the energy consumption, Lora/NB-IoT-based network structures, and data usage strategies. This IoT-based insulation condition monitoring is proven to be applicable for the distribution grid and expected to be referenced for more possible IoT applications.

Partial discharge detection method for vacuum leakage diagnosis of a vacuum interrupter

Vacuum circuit breakers (VCBs) have been widely used in the medium distribution voltage range of 12–38 kV for more than half a century. Recent interest for them is because of the loss of vacuum in a vacuum interrupter (VI). Generally, the leakage is an improbable event during the expected lifetime of typically 20–30 years, while there are some reports that VIs beyond their expected lifetime have a significantly higher leakage rate. To keep the high reliability of middle voltage VCB, even for the high voltage VCB, it is necessary to develop the earlier detection method of vacuum leakage from VI. In the present study, an experimental setup with a partial discharge (PD) detecting system for detecting vacuum leakage from a test VI was constructed. The internal pressure of VI was arbitrarily regulated in the range of 0.02–100 Pa through an insulating tube using several valves. A detecting resistor of 1 kΩ was connected to a plane electrode located outside 115 mm away from VI to measure the PD current due to discharges inside the VI. A current transformer (CT) was also placed below the plane electrode. Sensors with different specification for PD detection, such as a transient earth voltage sensor, a horn antenna, and an acoustic emission sensor, were investigated and characterized. As a result of pressure dependence of PD inception voltage, it follows the left side of Paschen's Law in the pressure range more than 2.0 Pa, while no discharges occurred below 2.0 Pa. To analyze the PD charge and rise time from measured waveforms, the PD mechanism in the medium voltage range inside the VI was discussed. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.