Insulation System Of Power Transformers Research Articles

Calculation of Charge Transport Phenomena and Mobility Analysis in the Insulating Oil Using First Principle and Marcus Theory.

Oil-paper insulation is widely used as a reliable composite insulation system in power transformers. The dielectric property of oil insulation plays an important role in the reliable operation of power equipment. To recognize the charge transfer process in composite insulation, the mobility of the charge in aged insulating oil is studied. However, few studies have been conducted on the microscopic mechanism of charge transport phenomena at the molecular level. In this research, we have studied the molecular electronic structure and the distribution of holes and electrons in the insulating oil by first-principles calculation. By combining with Marcus theory, the corresponding electron coupling energy, reorganization energy, and free energy are obtained. The corresponding charge hopping model is chosen by the parameter relation, and the hopping rate is calculated. At last, the mobility of holes and electrons in insulating oil within the insulation is simulated by the Monte Carlo method. Other possible charge migration methods are also studied and discussed for the comparison. It is observed that the transfer integral of electrons is 2 orders of magnitude larger than that of holes, which is mostly due to the localization of lowest unoccupied molecular orbitals (LUMO). The hole and charge transfers accord with Marcus hopping, the adiabatic charge transfer model, and the charge hopping rate is obtained. The actual free energy action under an external electric field is obtained by calculating polarizability and permittivity. Monte Carlo simulation is used to obtain the charge transfer image and mobility under an actual electric field. Possible types of traps and mobility of ions and clusters in the insulating oil are also studied.

Transformer hot spot temperature estimation through adaptive neuro fuzzy inference system approach

Transformer performance and efficiency can be enhanced by effectively address the properties of its insulation system. The power transformer insulation system weakens as a result of operational thermal stresses brought on by dynamic loading and shifting environmental patterns. Winding hot spot temperature is a crucial metric that must be maintained below the prescribed limit while power transformers are operating so as to maintained power system reliability. This is due to the fact that, among other variables, the time-dependent aging effect of insulation depends on transitions in hot spot temperatures. Due to the non‐linear nature of the conventional mathematical models used to determine these temperatures, and complexity of thermal phenomena, investigations still need to be exercised to fully understand the variables that associate with hot spot temperature computation with minimum error. This paper explores the possibilities of enhancing top oil and hot spot temperature estimation accuracy through the use of an adaptive neuro-fuzzy inference (ANFIS) technique. The paper presents an adaptive neuro fuzzy model to approximate the hot spot temperature of a mineral oil-filled power transformer based on loading, and established top oil temperature. Initially, a sub-ANFIS top oil temperature estimation model based on loading and ambient temperature as inputs is established. Using a hybrid optimization technique, the ANFIS membership functions were fine-tuned throughout the training process to reduce the difference between the actual and anticipated outcomes. The correctness and reliability of the created adaptive neural fuzzy model have been verified using real-world field data from a 60/90MVA, 132 kV power transformers under dynamic operating regimes. The ANFIS model results were validated against field measured values and literature-based electrical-thermal analogous models, establishing a precise input-output correlation. The developed ANFIS model achieves the highest coefficient of determination for both TOT and HST (0.98 and 0.96) and the lowest mean square error (7.8 and 10.3) among the compared thermal models. Correct determination of HST can help asset managers in thermal analysis trending of the in-service transformers, helping them to make proper loading recommendations for safeguarding the asset.

A Comparison Between Bubble Formation on Kraft and Thermally Upgraded Papers in Synthetic Ester

Bubble formation endangers the integrity of the oil-paper insulation system of power transformers. In this research, a test setup is created to detect bubbling inception temperature (BIT) for Kraft and thermally upgraded papers (TUPs). The paper samples are dried, prepared at six different moisture levels, and immersed in synthetic ester for the experiments. The paper strips are wound around a cartridge heater, and a controller unit raises its temperature. Results of the experiments revealed that BITs for Kraft paper are comparable to those reported in the literature. Usage of synthetic ester is shown to cause insignificant changes in the BITs. The causes of discrepancies among the BITs obtained via different test setups are discussed in detail, and an equation is presented to estimate BIT in Kraft paper based on four experimental data sets. The tested TUP is shown to have significantly lower BITs than Kraft paper, which is in contrast to the previously reported data. Scrutinizing TUP at temperatures beyond BITs revealed that the behavior of bubble formation differs from that in the Kraft paper. In the test setup with Kraft paper, bubbles are formed progressively at temperatures higher than BIT. In contrast, occasional sporadic bubbles emerge from TUP beyond the BIT until a stream of bubbles, similar to the case of Kraft paper, is observed at several degrees higher than BIT in the TUP.

Bubbling Phenomena in Liquid-Filled Transformers: Background and Assessment

The degradation of the insulation system in liquid-filled power transformers is a serious concern for electric power utilities. The insulation system’s ageing is accelerated by moisture, acids, oxidation products, and other decay particles (soluble and colloidal). The presence of these ageing by-products is detrimental to the insulation system and may further lead to premature ageing and serious consequences. The ageing mechanisms of oil-paper insulation are complex, highly interrelated, and strongly temperature-dependent. The operating temperature of the transformer insulating system has a direct relationship with the loading profile. The major aspect that is witnessed with the fluctuating temperatures is moisture migration and subsequent bubble evolution. In other words, gas bubbles evolve from the release of water vapor from the cellulosic insulation wrapped around the transformer windings. The models presented in the existing standards, such as the IEC Std. 60076-7:2018 and the IEEE Std. C57.91:2011, are mainly based on the insulation temperature, which acts as a key parameter. Several studies have investigated the moisture dynamics and bubbling phenomenon as a function of the water content in the paper and the state of the insulation system. Some studies have reported different prototypes for the estimation of the bubble inception temperatures under selected conditions. However, there are various attributes of the insulation system that are to be considered, especially when expanding the models for the alternative liquids. This paper reviews various evaluation models reported in the literature that help understand the bubbling phenomenon in transformer insulation. The discussions also keep us in the loop on the estimation of bubbling behavior in alternative dielectric liquids and key attributable factors for use in transformers. In addition, useful tutorial elements focusing on the bubbling issue in transformers as well as some critical analyses are addressed for future research on this topic.

Frequency Range of UHF PD Measurements in Power Transformers

Although partial discharge (PD) measurement is a well-accepted technology to assess the quality of the insulation system of power transformers, there are still uncertainties about which frequency range PDs radiate and which frequency range should be evaluated in a measurement. This paper discusses both a UHF PD frequency range obtained from studies investigating laboratory experiments and a frequency range from numerous practical use cases with online and on-site measurements. The literature review reveals a frequency spectrum of ultrahigh-frequency (UHF) PD measurements in the range of 200 MHz to 1 GHz for most publications. Newer publications extend this range from 3 to 6 GHz. The use cases present UHF PD measurements at transformers with power ratings up to 1000 MVA to determine frequency ranges which are considered effective for practical applications. The “common” frequency range, where measurements from all use cases provide signal power, is from approximately 400 MHz to 900 MHz, but it is noted that the individual frequency range, as well as the peak UHF signal power, strongly varies from case to case. We conclude from the discussed laboratory experiments and practical observations that UHF PD measurements in power transformers using either valve or window antennas, according to Cigré, are feasible methods to detect PD.

Effect of Electrical Accelerated Aging on DC Resistivity of Mineral Oil Used in Power Transformers

Power transformers are still equipment of primary importance within power grids. The recent paradigm changes registered in the field of energy require the interconnection of electrical grids of much larger areas, even up to the level of an entire continent. In this context, knowing the state of the electrical equipment and that of the power transformers is an essential aspect to ensure safe operation conditions. The present work is related to the vulnerability of the oil–paper insulation systems of power transformers to different aging factors and their quick degradation under certain conditions. In this regard, the study proposed in this paper considers the measurement of DC resistivity on mineral oil samples contaminated with small amounts of accelerated aging oil under the action of high-strength electric field and partial discharges. In the absence of standardized procedures for accelerated electrical aging of mineral oil, an original method presented and discussed in previous articles is used. The obtained results clearly indicate that under the action of electrical stress, the mineral oil resistivity decreases significantly, showing that the oil’s electric properties worsen.

Experimental Study of Sealed Tube Accelerated Aging Test Parameters and Determination of the Thermal Class of Transformerboard

The latest 2011 edition of the IEEE C57.100 standard introduced a new sealed tube accelerated aging test (STAAT) procedure and methodology for evaluating the thermal index (TI) of liquid-immersed transformer insulation systems. The application of this standard becomes increasingly important, as new insulating materials (both solid and liquid) have been developed, and their thermal performance shall be qualified. The experimental work presented in this article investigated the effects of different test parameters on the aging test results and data interpretation. The new findings on the dependence of the aging process on the ratio and type of materials in the system, as well as on the selected aging criteria provide a better understanding of the accelerated aging and interpretation of the data along with practical recommendations for the improvement of the test procedure. In parallel, for the first time, the TI of the Transformerboard, as a component of the so-called industry-proven insulation system, was investigated and defined based on the standard industry test. The results confirmed that the Transformerboard’s thermal class is, at least, 120 °C; this validates an empirically based application of this material as a part of the 120 °C class insulation system in both power and distribution transformers.

The detection and classification of partial discharges in power transformer using the acoustic method

Partial discharges are the main causes of degradation of the insulation system in power transformers. Their permanent monitoring is therefore of fundamental importance, in the way that it ensures a better assessment of the level of electrical insulation. Several types of partial discharges are present in power transformers depending on the components of the electric field to which the insulation is subjected. Many on-line methods are used to the continuous measurement of partial discharges, including the acoustic method which doing both measurement of electrical parameters and localization of the sources of partial discharges. This article deals with both recognition and classification of partial discharges by analysis of acoustic signals. The goal is to reproduce various types of partial discharges present in the transformers (surface, internal, and corona discharges) by several structures of electrodes in a prototype transformer filled with insulating oil. The generation of partial discharges is done using an experimental setup consisting of a controlled 220V/50kV HV transformer connected to a prototype of transformer containing an electrode system. The experimental procedure are carried out according to the protocol of the IEC 61270 standard. The measurement of the acoustic signals on the tank is carried out using a conventional broadband sensor from the company ACOUSTIC EMISSION (GI150). Both signal analysis obtained in the frequency domain using the time-frequency response and high-resolution frequency analysis (MUSIC) makes it possible to clearly distinguish the type of discharge produced.

Dielectric Response Model for Transformer Insulation Using Frequency Domain Spectroscopy and Vector Fitting

This paper proposes a rational approximation-based approach to find positive real parameters for the extended Debye model (EDM), aimed at condition assessment of insulation systems of power transformers. The EDM can model the slow and fast polarization phenomenon, including relaxation mechanisms with different relaxation times within a composite dielectric material. In the proposed approach, the complex permittivity of the transformer’s composite insulation is approximated via rational functions, as given by the vector fitting (VF) software tool, and the EDM parameters are identified from the obtained poles/residues. To guarantee positive real parameters, i.e., a physically realizable circuit, VF is internally modified to calculate the final residues of the rational approximation via a constrained linear least-squares problem without resorting to further post-processing algorithms, as in existing methods, hence without affecting fitting accuracy. The effectiveness of the parametrized EDM is demonstrated in two ways: (a) by reconstructing frequency domain spectroscopy (FDS) curves provided via measurements in new oil-immersed power transformers and (b) by the comparison of the calculated polarization current given by EDM versus real measurements in time domain. The achieved fitting accuracy in most of the cases is above 99 percent for the reconstructed FDS curves, while the polarization current waveform is reproduced with good agreement.

Nonlinear Dielectric Properties of the Stator and Transformer Insulation Systems

Composite insulation systems usually exhibit nonlinear phenomena, such as voltage-dependent dielectric response and high-order current harmonics. In this article, a high-voltage system capable of performing both dielectric frequency response (DFR) and polarization/depolarization current (PDC) measurements up to 20 kV is devised. The nonlinear properties of the motor stator and power transformer insulation systems are studied. Experimental results show that the voltage-dependent effect becomes significant as the voltage magnitude approaches the nominal and frequency decreases. The third current harmonic component is found to be dominant over the other components and has a strong correlation with the decrease in the dissipation factor. By taking both the fundamental and third-harmonic components into account, more consistent voltage-dependent characteristics are revealed. These features are important indications of insulation defects that are often neglected in field diagnostic testings. The investigation of the nonlinear properties helps to enhance the condition diagnosis reliability.

Analysis of Transformer Oil-Paper Insulation State Using Fractional Poynting-Thomson Model

This article is aimed at quantifying the health condition of the power transformer insulation system through its frequency-domain dielectric characteristic by using the concept of the resistor and fractional calculus. In this regard, the dielectric model of the fractional Poynting–Thomson (PT) is proposed, and a mathematical model for parameter identification of the proposed model is presented. The shuffled frog leaping algorithm (SFLA) is used to realize the parameter identification and the fractional PT model parameters of the oil-paper samples under different insulation health conditions. The influence of moisture and aging on the fractional PT dielectric model parameters is experimentally studied. Results show that, with the increase in the water content within the insulation system, the parameters of the fractional PT model gradually decrease, and there is a strong correlation between the relaxation time and the water content. This facilitates the employment of the fractional PT model parameters to quantify the aging and moisture content of the power transformer insulation system.

Kinetic Assessment of Mechanical Properties of a Cellulose Board Aged in Mineral Oil and Synthetic Ester.

In oil-immersed power transformers, the insulation system is constituted of a dielectric oil–solid combination. The insulation oil generally used is mineral oil; however, this fluid has started to be substituted by natural and synthetic esters due to their higher biodegradability and flash point. The introduction of a new fluid in the insulation system of power transformers requires kinetic models that can estimate the degradation rate of insulation solids. The aim of this work was to go further in quantifying through different kinetic models the deterioration suffered by a commercial cellulose board (PSP 3055), which is one of the solid materials used in the insulation system of oil-filled transformers. The aging study was extended to cellulose board specimens immersed in two different oils (mineral and synthetic ester). It was obtained that there is a lower degradation when synthetic ester is used in the insulation system. Additionally, it can be concluded that the use of mechanical properties to quantify the degradation of the cellulose board through kinetic models provides information about the different behavior shown by PSP 3055 when different fiber direction angles are considered.

Application of Molecular Sieves for Drying Transformers Insulated with Mineral Oil, Natural Ester, or Synthetic Ester

A high level of moisture in the insulation system of power transformers is often the cause of their failure. This can be prevented by drying a transformer in its place of installation. In the article the application of molecular sieves (MS) in the drying process of the transformer insulation system was analyzed. The water sorption isotherms of 3A MS in mineral oil, natural ester, and synthetic ester at 35 °C were determined, which was not described in the literature before. An evaluation of the influence of temperature on the drying dynamics of electro-insulating liquids using MS was also carried out. The drying dynamics were tested at three temperatures, i.e., 35 °C, 50 °C, and 65 °C, which allowed to analyze the effect of temperature on a short-term or continuous drying process. The tests showed that 3A MS’s ability to adsorb water varied depending on the type of electro-insulating liquid. The determined water sorption isotherms, described by means of Langmuir adsorption model, make it possible to calculate the amount of MS needed for drying transformers with different liquid insulation. The research and analyses show the MS’s great potential for the drying of transformer insulation systems.

Portable NIR Spectroscopy Measuring Device for Transformer Oil DBPC Inhibitor Analysis

Monitoring the insulation system of power transformers is crucial in ensuring power transformers are operating in optimal conditions. Given the nondirect and destructive nature of conventional techniques, optical techniques have prevailed to be an effective alternative to monitor the condition of the insulation system. The recent development of small and compact optical components has also contributed to the utilization of optical techniques in onsite testing and online monitoring application. Therefore, this work proposed the measurement of inhibitor concentration in transformer oil by using a portable optical measuring device that utilizes near-infrared spectroscopy. The fundamental studies of measuring inhibitor in transformer oil by using a newly discovered wavelength at 1403 nm were validated, and its adaptation to a portable optical measuring device was discussed. A new mathematical model was formulated to estimate the inhibitor concentration in transformer oil samples on the basis of data obtained from the photodetector. Measurements and the conventional technique were conducted for performance comparison and prototype verification. Results showed a root-mean-square-error of 0.01708 and an average error of 2.11%. This proposed prototype opens up opportunities in onsite testing and online monitoring of inhibitor content concentration in transformer oil.

Dealing With Data Uncertainty for Transformer Insulation System Health Index

Health index has been widely accepted as a powerful tool for monitoring the condition of power transformer insulation system based on various diagnostic parameters. While this approach has been extensively discussed in the literature, not much attention was given to provide effective solutions to the uncertainty in the used data. According to CIGRE 761, data quality issues may arise due to measurement accuracy as well as incompleteness and unavailability of the required data. Therefore, this article presents the implementation and evaluation of a certainty level model for transformer insulation system health index to deal with data uncertainty. The impact of data unavailability on the health index results is also investigated. Certainty level of the health index is determined by the criticality level of available data, and is reported along with the health index result. A method to handle unavailable data by predicting the oil interfacial tension (IFT) using Random Forest approach is also presented. The proposed certainty level model is designed to accommodate the predicted value of missed data into the health index model while considering its prediction accuracy. The robustness of the developed model is validated through its application in assessing the health condition of six in-service power transformers. The results indicate that by including the proposed certainty level and the prediction approach to eliminate the issue of uncertain and missed diagnostic data, an asset management decision can be taken on operating power transformer fleets with high level of confidence.

Artificial Intelligence-Based Power Transformer Health Index for Handling Data Uncertainty

Power transformer is a critical and expensive asset in electric transmission and distribution networks. It is essential to monitor the health condition of all power transformer fleet in such networks to avoid unwanted outages. The health index (HI) is a quick and efficient way to assess the condition of power transformers based on multi-criteria. While Power transformer HI method has been well presented in the literature, not much attention was given to handle the uncertainty and reliability of this method due to unavailability of used data. Therefore, this paper aims to tackle this issue through employing Artificial Intelligence (AI)-based techniques to reveal the health condition of power transformers with high accuracy and at the same time handling data uncertainty. The proposed HI approach assesses the power transformer insulation system based on oil quality, dissolved gas analysis (DGA), and paper condition. In this regard, collected data from 504, 150-kV transformers are used to establish the proposed AI-models. Seven AI algorithms including k-Nearest Neighbor (kNN), Support Vector Machine (SVM), Random Forest (RF), Naive Bayes (NB), Artificial Neural Network (ANN), Adaptive Boosting (AdaBoost), and Decision Tree are investigated. A performance comparison of the proposed AI-based HI models is carried out using the scoring-weighting-based HI method as the reference. Results show that RF model provides the best performance in predicting power transformer HI with an accuracy of 97.3%.

Method for Rating and Analyzing the Combined Effects of Moisture and Temperature on the Oil–Paper Insulation System of Power Transformers by Means of Load Variations

This paper presents an innovative method devised to study some of the harmful effects of moisture on power transformers, considering the possible formation of bubbles and free water. Its novelty stems from the fact that it comprises: (a) a rating system from “A” to “E” and their respective recommended actions and (b) an analysis that involves varying the different levels of electrical loads applied to the equipment. The importance of this work is confirmed when power transformers are exposed to unfavorable conditions that can critically affect their insulation. To this end, a tool to study moisture was developed, which uses the finite difference method, based not only on the experience of experts/analysts but also on existing studies in the area and on the analysis of a database of actual field tests. The contribution of this work is an efficient method, implemented via a computational algorithm, which provides a technique for the real-time or offline rating of power transformers, helping maintenance teams to diagnose problems and decide whether or not to repair the equipment. The tool provided the satisfactory results, which are presented in a case study of a real transformer operating at the local electric utility company. These results were obtained by applying different levels of electrical loads, for which thermal simulations were performed.

Streaming Electrification Phenomenon of Electrical Insulating Oils for Power Transformers

The subject matter of this study was the problem of the ECT (electrostatic charging tendency) of mineral insulation oils during their flow. The electrostatic charges generated may lead to partial discharges, and as a consequence, to the breakdown of a power transformer insulation system. In this study, the results of the ECT of mineral oils used in transformers were compared. The method of streaming electrification of insulation liquids using a flow-through system was used. The influence of flow speed, temperature, and the pipe material on the values of the electrification current and volume charge density qw were analyzed. The results obtained in this study should be taken into account regarding the operation of power transformers.

Analysis of Internal Overvoltages in Transformer Windings during Transients in Electrical Networks

Due to the increasing requirements for the reliability of electrical power supply and associated apparatus, it is necessary to provide a detailed analysis of the overvoltage risk of power transformer insulation systems and equipment connected to their terminals. Exposure of transformer windings to overvoltages is the result of the propagation condition of electromagnetic waves in electrical networks and transformer windings. An analysis of transformer winding responses to transients in power systems is of particular importance, especially when protection against surges by typical overvoltage protection systems is applied. The analysis of internal overvoltages in transformers during a typical transient related to switching operations and selected failures is of great importance, particularly to assess the overvoltage exposure of insulation systems in operating conditions. The random nature of overvoltage phenomena in electrical networks implies the usage of computer simulations for the analysis of overvoltage exposures of electrical devices in operation. This article presents the analysis of the impact of transient phenomena in a model of a medium-voltage electrical network during switching operations and ground faults on overvoltages in the internal insulation systems of transformer windings. The basis of the analysis is simulations of overvoltages in the windings, made in the Electromagnetic Transients Program/Alternative Transients Program (EMTP/ATP) using a model with lumped parameters of transformer windings. The analysis covers the impact of the cable line length and the ground fault resistance value on internal overvoltage distributions.

Application of Polarization and Depolarization Current in High Voltage Insulator - A Review

Deterioration of cable insulator can be caused by many factors such as aging, fault and breakdown. These factors are caused by the presence of moisture, impurities and heat due to high temperatures in an insulator. The maintenance and replacement for insulation system in power cables, power transformers and electric machine stator are generally expensive and time consuming. Thus, the performance and ability of an insulator can be monitored through polarization and depolarization current (PDC). Polarization and depolarization current (PDC) is a non- destructive test method that is used to analyse many factors that affects the behaviour of an insulator in time domain. This paper presents the review on application of polarization and depolarization current test method on different type of insulator. The factors that affects the performance of different type of insulator will be discussed in this paper. Moreover, the theory of polarization and depolarization current will be explained in order to understand the behaviour of polarization and depolarization current curve when fault occurs. Last but not least, this paper will provide a review on the different type of factors that affects the performance of different types of insulation.