High Voltage Apparatus Research Articles

Calculation of electron-impact ionization cross sections of perfluoroketone (PFK) molecules CxF2xO (x = 1–5) based on Binary-Encounter-Bethe (BEB) and Deutsch-Märk (DM) methods

Perfluoroketone (PFK) gases are widely used in industry, e.g. as an insulating medium in high-voltage apparatus and as a cleaning agent in chemical vapor deposition (CVD) chambers. A great deal of attention has been paid to them recently because of their low global warming potential (GWP). In order to describe the ionization processes in various plasmas resulting from PFK gases, the electron-impact ionization cross sections (Qion) of PFK molecules CxF2xO (x = 1–5) were calculated by the Binary-Encounter Bethe (BEB) and the Deutsch-Märk (DM) methods. The chemical structures of PFK molecules were optimized by the hybrid Density Functional Theory (DFT) method with the Austin-Petersson-Frisch functional including dispersion (APF-D). The binding and kinetic energies of electrons in molecular orbitals were also determined with the APF-D hybrid DFT method. The binding energies of valence electrons were then improved by the electron propagator theory (EPT) method. The ionization potentials of PFK molecules were calculated as the difference between the energy of a molecule and its cation using the complete basis set (CBS) method. The molecular orbital compositions were obtained by the natural atomic orbital (NAO) analysis. The results show that Qion determined by the BEB method are always larger than those by the DM method. The difference is reduced with the EPT corrections considered. The comparison between the theoretical and experimental Qion demonstrates that the EPT correction improves Qion considerably.

Towards automated statistical partial discharge source classification using pattern recognition techniques

This study presents a comprehensive review of the automated classification in partial discharge (PD) source identification and probabilistic interpretation of the classification results based on the relationship between the variation of the phase-resolved PD (PRPD) patterns and the source of the PD. The proposed automated classification system consists of modern, high-performance statistical feature extraction methods and classifier algorithms. Their application in online monitoring and recognition of the PD patterns is investigated based on their low-processing time and high-performance evaluation. The application of modern statistical algorithms and pre-processing methods configured in this automated classification system improves the pattern recognition accuracy of the different PD sources that are suitable to be employed in different high-voltage (HV) insulation media. To evaluate the performance of the different combinations of the feature extraction/classier pairs, laboratory setups are designed and built that simulate various types of PDs. The test cells include three sources of PD in , two sources of PD in transformer oil, and corona in the air. Data samples for different classes of PD sources are captured under two levels of voltage and two different levels of noise. The results of this study evaluate the suitability of the proposed classification systems for probabilistic source identification in various insulation media. Furthermore, of importance to the problem of the PD source identification is to assign a ‘degree of membership’ to each PRPD pattern, besides assigning a class label to it. Some of the classifier algorithms studied in this study, such as fuzzy classifiers, are not only able to show high classification accuracy rate, but they also calculate the ‘degree of membership’ of a sample to a class of data. This enables probabilistic interpretation of a new PRPD pattern that is being classified. The determination of the degree of membership for future PRPD samples allows safer decision making based on the risk associated with the different sources of PD in HV apparatus.

Dielectric properties of fluoronitriles/CO2 and SF6/N2 mixtures as a possible SF6-substitute gas

Perfluoronitriles (PFN) and their mixtures have garnered much attention as a great potential SF 6 -substitute gas, owing to their excellent dielectric strengths and minimal impacts on the environment. The dielectric properties of C4-PFN/CO 2 and SF 6 /N 2 mixtures are investigated and compared by experiments and calculations, with taking into account the limitations of saturated vapor pressure on the mixed ratio at certain ambient temperatures. The saturated vapor pressures of these two mixtures are determined by combining the Antoine Equation and the basic law of vapor liquid equilibrium. Then, the 50% breakdown voltages V 50% of the C4-PFN/CO 2 and SF 6 /N 2 mixtures are determined by tests with up-and-down method, and the values of E/p are deduced. Finally, the dielectric properties of these two mixtures are analyzed by combining the saturated vapor pressure characteristics and the breakdown electric field strengths. The results show that a proper choice of the mixed ratio and gas pressure of the C4-PFN/CO 2 mixture can provide a stronger DS than the SF 6 /N 2 mixture and pure SF 6 . This indicates a great potential of the C4-PFN/CO 2 mixture as a SF 6 -substitute gas for high voltage apparatus.

Measuring Method of the Internal Temperature of UHV DC Voltage Measuring Device

For many years, it has been difficult to measure the internal temperatures of gas insulated equipments in high voltage apparatuses. This paper presents a method of measuring the internal temperature of UHV DC Voltage measuring device, which uses the temperature sensor of fluorescent decay time optical fiber transmission as the instrument. The method could accurately measure the internal temperature when the device is running. The paper mostly expounds the selecting temperature sensor and arrangement mode of sensor and detailed test method. The test method could determine the internal temperature of UHV DC voltage measuring device, as the same time could also provide references for measuring the internal temperatures of gas insulated equipments in high voltage apparatuses.

Impact of Shape and Total of Particle to Characteristics of Partial Discharge and Breakdown Voltage on Oil Insulation in Uniform Field

Oil insulation is one of the insulation medium types commonly used in high voltage apparatus. This insulation is to separate between the conductive part and non-conductive part. However, oil insulation can experience decreasing of dielectric strength. It may be caused by the presence of solid particles. Therefore, the testing was conducted to obtain the effect of solid particles to characteristics of partial discharge and breakdown voltage of oil insulation. The results generally proved that the existence of solid particles can reduce the breakdown voltage value of oil insulation. In addition, the solid particles led to two types of corona on oil insulation, namely positive and negative corona.

Prediction of insulating transformer oils breakdown voltage considering barrier effect based on artificial neural networks

The insulating oil performance could be enhanced in high-voltage apparatus using barriers. The importance of the barrier in increasing the dielectric strength of the insulating oils in order to reduce the oil failure stresses had not been sufficiently studied. In this paper, the effects of the barrier variables on the insulation performance of the transformer oil for point-plate and plate-plate gaps were demonstrated. These variables are: gap space (d), the barrier location relative to the high-voltage electrode (a / d) %, barrier diameter (D), barrier thickness (e), electrode configurations (EC), the presence of contaminating particles, the weight of the contaminating particles (W) and the temperature of the insulating oil (T). The statistical t test was used to explain whether the effect of these parameters was significant or not. Furthermore, the above-mentioned variables were used as training variables to construct the prediction model of oil breakdown voltage considering barrier effect based on the artificial neural networks (ANN). The ANN model was developed based on the results from experimental works. Therefore, 784 samples were used as training data set and other 25 samples were taken as testing and validating samples. The results explained that the prediction ANN model had a high ability to expect the breakdown voltage for other different experiment cases. The average errors of the training and testing samples were 1.6%, and 2.66%, respectively. Therefore, the prediction accuracy could be considered as 98.4% for training and 97.34% for testing.

Analysis of Electric Field and Current Density for Different Electrode Configuration of XLPE Insulation

The most important aspect influencing the circumstance and characteristics of electrical discharges is the distribution of electric field in the gap of electrodes. The study of discharge performance requires details on the variation of maximum electric field around the electrode. In electrical power system, the insulation of high voltage power system usually subjected with high electric field. The high electric field causes the degradation performance of insulation and electrical breakdown start to occur. Generally, the standard sphere gaps widely used for protective device in electrical power equipment. This project is study about the electric field distribution and current density for different electrode configuration with XLPE barrier. Hence, the different electrode configuration influences the electric field distribution. This project mainly involves the simulation in order to evaluate the maximum electric field for different electrode configuration. Finite Element Method (FEM) software has been used in this project to perform the simulation. This project also discusses the breakdown characteristics of the XLPE. The accurate evaluation of electric field distribution and maximum electric field is an essential for the determination of discharge behavior of high voltage apparatus and components. The degree of uniformity is very low for pointed rod-plane when compared to other two electrode configurations. The non- uniform electric distribution creates electrical stress within the surface of dielectric barrier. As a conclusion, when the gap distance between the electrodes increase the electric field decrease.

Creepage Discharge Characteristics of Solid Insulation Materials for Superconducting Power Cable

Solid insulation materials need to be robust in terms of both mechanical and electrical performance for application in a high-voltage superconducting apparatus. It is known that creepage discharge characteristics of solid insulation materials are inferior to their electrical breakdown characteristics with penetration. Therefore, electrical breakdown accidents in a superconducting apparatus could occur as a form of creepage discharge rather than electrical breakdown with penetration. In this study, we conduct dielectric experiments on the penetration and creepage discharge characteristics of epoxy resin and polypropylene laminated paper under cryogenic temperature by using three kinds of electrode systems. The first is for creepage discharge experiments along the surfaces of solid insulation materials in liquid nitrogen. The second is for creepage discharge experiments across the interface between two different solid insulation materials making contact in liquid nitrogen. The third is for experiments of electrical breakdown with penetration on solid insulation materials in liquid nitrogen. Dielectric experiments are conducted with an absolute pressure of 0.1 MPa under alternating current and lightning impulse voltages. Experimental results for electrical breakdown characteristics of solid insulation materials with penetration are compared with the creepage discharge characteristics on the surface and interfaces between solid insulation materials. Moreover, the criteria for electric field intensities at creepage discharge voltages in various conditions are deduced as empirical formulas.

DEIS distinguished lecturer program november 2017 - workshop

A workshop was conducted by Professor Toshikatsu Tanaka from Waseda University, Japan, on November 7, 2017, at the Institute of High Voltage and High Current, Universiti Teknologi Malaysia, Johor Bahru, Malaysia, in conjunction with the DEIS Distinguished Lecturer Program. The workshop began with Professor Tanaka’s presentation titled “Dielectric Polymer Aging Phenomena and Diagnostics in High Voltage Engineering.” Thirty-one participants from academia and industry were introduced clearly to various aging phenomena in polymeric insulators, e.g., partial discharge, treeing breakdown, tracking, and thermal degradation. Professor Tanaka also discussed various diagnostic methods used in high voltage engineering, and described common insulation diagnostics practice in Japan for high voltage apparatus such as cables, transformers, and gasinsulated switchgears.

Synchronized Wireless Measurement of High-Voltage Power System Frequency Using Mobile Embedded Systems

This paper focuses on synchronized wireless measurement of high-voltage (HV) power system frequency using mobile embedded systems (MESs) integrated with a wireless electric field sensor (WEFS). Unlike traditional synchronized frequency measurement devices, which rely on potential transformers and current transformers physically connected to system elements, a WEFS is used to realize wireless signal acquisition in the vicinity of any HV apparatus. The MES performs real-time frequency estimation using a recursive discrete Fourier transform based algorithm. Network time protocol (NTP) is used for time synchronization, increasing the system flexibility by eliminating global positioning system reliance. An NTP-based synchronized sampling control method is proposed and implemented in MES to compensate the sampling time error caused by local time drift and division residue. The proposed system has the advantages of portability and lower cost, making it highly accessible and useful for a wide array of synchronized frequency measurement applications. Experiment results verify the accuracy and effectiveness of the proposed system.

Influence of Conductive and Semi-Conductive Nanoparticles on the Dielectric Response of Natural Ester-Based Nanofluid Insulation

Nowadays, studies of alternative liquid insulation in high voltage apparatus have become increasingly important due to higher concerns regarding safety, sustainable resources and environmentally friendly issues. To fulfil this demand, natural ester has been extensively studied and it can become a potential product to replace mineral oil in power transformers. In addition, the incorporation of nanoparticles has been remarkable in producing improved characteristics of insulating oil. Although much extensive research has been carried out, there is no general agreement on the influence on the dielectric response of base oil due to the addition of different amounts and conductivity types of nanoparticle concentrations. Therefore, in this work, a natural ester-based nanofluid was prepared by a two-step method using iron oxide (Fe2O3) and titanium dioxide (TiO2) as the conductive and semi-conductive nanoparticles, respectively. The concentration amount of each nanoparticle types was varied at 0.01, 0.1 and 1.0 g/L. The nanofluid samples were characterised by visual inspection, morphology and the dynamic light scattering (DLS) method before the dielectric response measurement was carried out for frequency-dependent spectroscopy (FDS), current-voltage (I-V), and dielectric breakdown (BD) strength. The results show that the dielectric spectra and I-V curves of nanofluid-based iron oxide increases with the increase of iron oxide nanoparticle loading, while for titanium dioxide, it exhibits a decreasing response. The dielectric BD strength is enhanced for both types of nanoparticles at 0.01 g/L concentration. However, the increasing amount of nanoparticles at 0.1 and 1.0 g/L led to a contrary dielectric BD response. Thus, the results indicate that the augmentation of conductive nanoparticles in the suspension can lead to overlapping mechanisms. Consequently, this reduces the BD strength compared to pristine materials during electron injection in high electric fields.

Electric field evaluation and optimization of shielding electrodes for high voltage apparatus in ±1100 kV indoor DC yard

The indoor DC yard of the ±1100 kV UHVDC transmission project is preferred to the outdoor solution, and the rational design of shielding electrodes for the ±1100 kV apparatus becomes the key to system security. In this paper, the design requirements of indoor DC yards were described and the preliminary designs of the indoor shielding electrodes for the key ±1100 kV DC apparatus were proposed. The whole 3-D FEM model of one ±1100 kV indoor DC yard was established. An empirical formula of the critical E-field strength for the evaluation of relatively large shielding electrodes was proposed based on the corona tests of typical ball and ring electrodes. The electric field distribution of the whole indoor DC yard was calculated and the surface electric field strength of all the shielding electrodes for the key ±1100 kV apparatus was evaluated. The results show that after optimization, the maximum surface field strength on the shielding electrode of ±1100 kV DC filter capacitor decreased from 1507 V/mm to 1335 V/mm, lower than the critical value for evaluation, then the corona free design of all the ±1100 kV indoor shielding electrode could be predicted. The method of electric field evaluation and optimization could provide important references for the development of shielding electrodes in the ±1100 kV or other UHV indoor DC yards.

Nonlinear effective permittivity of field grading composite dielectrics

Field grading composite dielectrics with good nonlinear electrical properties can function as smart materials for electrical field control in a high-voltage apparatus. Besides the well-documented nonlinear conducting behavior, the field-dependent effective permittivity of field grading composites were also reported; however, in-depth research on the mechanism and influencing factors of this nonlinear permittivity are absent. This paper theoretically discusses the origin of the nonlinear effective permittivity, and the mechanism is illustrated through the waveform analysis of the nonlinear response of ZnO microvaristor/silicone rubber composites under a pure AC field. The field-dependent effective permittivity and loss property of the ZnO composites are measured by a dielectric spectrometer in both DC and AC fields under different frequencies. Through comparison of measurement results and theoretical models, the influence of the filler concentration, frequency, and time domain characteristics of the applied field on the nonlinear permittivity of the field grading composites are well explained. This paper provides insight into the nonlinear permittivity of field grading composites, and will be helpful for further tuning the performance of field grading composites.

Grading electric field in high voltage insulation using composite materials

Localized overstress due to electric field concentration is a threat to the long-term performance of the insulation in almost all high voltage apparatus. Resistive field grading using field grading materials (FGMs) may be a solution to this problem. Insulation matrixes such as ethylene propylene diene monomer, epoxy, or silicone rubbers, blended with fillers such as ZnO microvaristors, are reported to possess field dependent conductivity with greater and more stable nonlinearity than traditional FGMs [1]. Their application in high voltage apparatus such as bushings [1], cable accessories [2]–[4], insulators [5], [6], and stator coils [7] has been studied recently. It is well known [8] that the most important parameters for FGMs are the nonlinear coefficient α and switching field Eb; the challenge is to tailor these two parameters to a specific application. FGMs can function effectively in most cases when α >10 [9], but the adjustment of Eb is more complex.

Acoustic and Electrical Detection to Localize And Measure the Partial Discharge in High Voltage Apparatus

The occurrence of the Partial Discharge (PD) inside the high voltage apparatus especially in power transformer due to some defect in its insulation system results in a catastrophic failure. Determination the magnitude and location of the PD inside the transformer is very valuable to avoid the undesired outage. In this paper, two important issues will discuss. The first issue, measuring the magnitude of the PD by the electrical detection device (The partial discharge analysis system MPD 600) that has many kits to the acquisition and analysis for detecting, recording and analyzing the PD. PD Measuring the circuit of MPD600 connected to point to plane according to IEC60270 with an optical interface by computer that have Metronix software in case of partial prediction. The second issue is determining the PD location to start the maintenance process. In order to locate the PD inside the transformer the acoustic signals that emit from the PD source were measured and therefore, the Time difference of arrival (TDOA) between these signals is estimated. A point to plan gap configuration that is mounted in the acrylic tank that contains the insulating oil is used to develop the PD point source. In addition four piezoelectric sensors are fitted on the tank walls to receive the acoustic signals. The sensors are coupled with acoustic PD detector which outputs are applied to four-channel digital oscilloscope to measure the acoustic signals. The proposed algorithm results demonstrate the ability of the algorithm to determine the PD location.

DC current capability of high voltage apparatus based on the open-core concept

Modular Multilevel Converters (MMC) HVDC converter station topologies require the use of high-impedance grounding reactors on the converter side of power transformers. The main requirement for such units is the ability to withstand simultaneous AC and DC loading. The aim of this paper is to give insight on how to determine the DC capabilities of such units both through calculation and measurements. Additionally, the purpose of this paper is to show what the possibilities of different core designs in terms of DC capability are and what values can be expected and obtained.

Study on the E-t Characteristics of GFRP for a High-Voltage Superconducting Apparatus

Power consumption has been increasing in industrial society [1]. The application of a superconducting apparatus is considered one of the most promising countermeasures against the increased power consumption. Additionally, the rated voltage of the superconducting apparatus has been being uprated to minimize the power loss. In order to ensure the electrical safety of a high-voltage superconducting apparatus, the dielectric design of solid insulation materials used in the high-voltage superconducting apparatus should be performed considering the aging characteristics. In this study, we examine the E-t characteristics of glass fiber reinforced plastic (GFRP), known to be one of the best solid insulation materials for cryogenic conditions [2]. Specifically, the E-t characteristics of GFRP according to its electric field uniformity are tested and analyzed to ensure the reliability of long-term operation. All the experiments are conducted in liquid nitrogen (LN2) to suppress the occurrence of creepage discharge and to promote the occurrence of electrical breakdown [3]. The experiments on the E-t characteristics of GFRP are performed with four kinds of sphere-plane electrode systems manufactured using stainless steel. The electric field uniformity and its relationship with electrical breakdown are analyzed using a finite element method, and the experimental results are analyzed using the Weibull distribution.

Coherence and time-frequency analysis of impulse voltage and current measurements

The aim of this paper is to point out the advantages of the use of the time-frequency analysis in the digital processing of waveforms recorded in high voltage impulse tests. Impulse voltage tests are essential to inspect and test insulation integrity of high voltage apparatus. On the other hand, generated impulse currents are used for different test applications such as investigation of high current effects, electromagnetic interference (EMI) testing, etc. Obtained voltage and current waveforms usually have some sort of interferences originated from the different sources. These interferences have to be removed from the original impulse data in order to evaluate the waveform characteristics precisely. When the interference level is high enough, it might not be possible to distinguish signal parameters from the recorded data. Conventional filtering methods cannot be useful for some interference like white noise. In that case, time-frequency filtering methods might be necessary. In this study, the wavelet analysis, which is a powerful time-frequency signal processing tool, is used to recognize the noise of impulse current and voltage data. Thus, the noise sources can be determined by short time Fourier Transform, and a coherence approach is used to determine the bandwidth of noises.

Identification and localization of PD-sources in power-transformers and power-generators

Partial discharge (PD) measurements are in use since more than 50 years with the aim to assess the condition of the insulation systems of high voltage (HV) apparatus and components. In large power transformers and power generators, PD-sources can be situated well hidden inside complex insulation systems. For PD-sources inside the active parts of such systems, measured values of the apparent charge in pC/nC do not sufficiently reflect the real risk of these defects. This is mainly due to the strong attenuation and deterioration of the PD-signals in such insulation systems. Therefore, continuous PD-activity detected at or below nominal voltage during a factory acceptance test, or recorded on-site by a monitoring system, may be harmful for a HV apparatus in service. In case of confirmed internal PD-activity, further investigation and localization should follow. Beside the analysis of simultaneously recorded PD-patterns at all terminals, the evaluation of PD-signals in the time-domain and frequency-domain offers a considerable potential to localize internal PD-sources in extended insulation systems. PD-signals detected at the terminals of a transformer or generator contain information about their propagation paths from the unknown location of the PD-source to the specific sensor. This contribution describes both, the advanced PD-measuring techniques and procedures for identification and localization of PD-sources. The advantages and limits of PD-signal analysis in the time- and frequency-domain are discussed using practical examples.

Classification of simultaneous multiple partial discharge sources based on probabilistic interpretation using a two-step logistic regression algorithm

In online condition assessment monitoring of high voltage (HV) insulators, it is often required to identify multiple, simultaneously activated partial discharge (PD) sources that happen in the insulation of the HV apparatus. Phased resolved partial discharge (PRPD) patterns are commonly used to identify PD sources. However, multiple, concurrent PD sources sometimes result in partially overlapped patterns, which make them hard to be identified. In this paper, we develop an accurate, reliable algorithm by constructing a novel two-step logistic regression (LR) model to conduct probabilistic identification of multi-source PDs. To this end, principal component analysis is applied on a database to construct a low dimensional space associated with single-source PDs. Samples of multi-source PDs are then projected onto this space and one-class kernel support vector machine is adopted to distinguish multi-source PDs from single-source ones. Finally, classification is performed by estimating the probability (degree of membership) of each PRPD pattern arising from different multi-source PDs following two rounds of LR modeling. To evaluate the performance of our proposed method, we study a number of multi-source PD models to simulate common defects of Gas-Insulated Switchgear (GIS) in small-scale laboratory test cells with realistic SF6 gas condition. Observations are obtained using fingerprints generated by a novel approach from recorded PRPD patterns. Comprehensive performance evaluation of the proposed algorithm and its advantages are conducted and the development of analytical equations is presented. The results of this paper can be used to design a solid basis for an automated multi-source classification system, which facilitates multi-source PD identification in early stages and safe operation of HV apparatus.