Actual Transformer Research Articles

Tank Current Measurement of Three-Phase Transformer: Its Resonance Behavior and Sensitivity to Detect Mechanical Faults

In this paper, a novel technique to improve the fault detection sensitivity in a three-phase transformer using the tank current method is reported. The tank current method was first published by the first author in recent past for single isolated transformer winding. A fault in single isolated transformer winding was uniquely identified employing the typical resonance behavior of tank current, but for three-phase transformer, such implementation is yet to be explored. The present scope of this paper is only for uniformly wound three-phase transformer windings. Implementing the tank current method for such a three-phase transformer may not be very simple, since the neighboring windings, unlike in the case of isolated winding, strongly influence the measurement of the tank current. Therefore, this paper appropriately considers the effect of neighboring windings in a three-phase transformer and investigates the resonance behavior of its tank current to propose a promising innovative extension approach of the method. Experimental results on actual transformers are also presented for practical validation of the proposed method. Results imply that the tank current method is indeed very sensitive to identify the fault in an actual transformer compared to the conventional neutral current method. The authors also believe that the method needs to be reinforced by field measurements on several transformers to ascertain its viability.

Finite-Element Modeling and Experimental Verification of Stray-Loss Reduction in Power Transformer Tank With Wall Shunt

The stray loss in a transformer structure is difficult to measure. Thus, it is very important to predict the loss accurately by numerical modeling. This article deals with numerical modeling and experiments for the prediction of the stray loss in power transformer tank. Before numerical analysis, the finite-element model should be verified in advance. In this article, results from finite element analysis (FEA) were compared with those from experiments by using a prototype model. Experiments were carried out by changing the wall shunt thickness by turns. The magnetic flux density obtained from the experiment is compared and agreed well with those predicted by 3-D FEA. After verifying the validity of FEA, the actual transformer was modeled and the wall shunt was applied to the tank to reduce the stray loss.

Conversion of RMS into Instantaneous Transformer Saturation Characteristics – Implementation in MATLAB/SPS-ST

The paper presents a reduced form of the algorithm for converting a measured RMS transformer characteristic into the corresponding peak instantaneous transformer saturation curve. The peak instantaneous saturation curve is an essential input for stationary and electromagnetic transient simulations of power systems such as harmonics, subharmonics, inrush currents, ferroresonance, load rejections and similar. The conversion algorithm was implemented in Saturable Transformer Block inside MATLAB/SPS-ST software. The existing transformer model in SPS-ST implies the need of knowing the saturation characteristic, which is generally absent in practice. Consequently, the RMS transformer characteristic was offered as an alternative to the actual core saturation characteristic in Saturable Transformer Block. A novel Saturable Transformer Block design tool, consisting of a graphical user interface, allows for a choice of either old saturation or novel RMS saturation characteristic. The developed transformer model with embedded conversion procedure was tested on an application example of transient and steady-state single-phase transformer simulation. It was exhibited that a novel Saturable Transformer Block produces identical simulation results to an actual Saturable Transformer Block. The new SPS-ST transformer model was further validated by laboratory measurements. The results of the transformer inrush current and steady-state current simulation and measurement showed a very good matching ratio. The developed algorithm for conversion of RMS into peak saturation characteristic applies to modeling and simulation of steady-state and transients in electrical systems, where voltage and current transformer, iron-cored reactors, nonlinear coil and electromagnetic ballast are the dominant elements.

Online monitoring and diagnosis method of transformer winding deformation

Winding deformation has become an important factor affecting the safe and stable operation of transformers. Parameters such as winding resistance, leakage inductance, and capacitance will change as a result of winding deformation. Therefore, a method of diagnosis of transformer winding deformation based on the above three parameters is proposed in this paper. An equivalent model of the transformer including winding resistance, leakage inductance, and equivalent capacitance is established. Online identification of the winding parameters is realized by the recursive least squares algorithm. Both the winding deformation classification and diagnosis of deformation degree are realized by using the winding parameters identified online. A simulation model of the actual transformer is established for verification and analysis. The results indicate that the method has high precision and overall correct rate. It meets the needs of online monitoring of winding deformation engineering. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Analytical Expressions to Link SCNF and OCNF of Transformer Windings to Their Inductances and Capacitances for 1-$\Phi$, 3-$\Phi$ Y and $\Delta$ Configurations

Recently, the present authors’ research group derived an analytical expression to link the harmonic sum of the squares of short circuit natural frequencies (SCNFs) of a single, isolated winding to its elementary inductances and capacitances. Also, it was demonstrated how this expression could be practically used for locating radial and axial displacements, along with assessing its severity on a single, isolated, actual transformer winding. The next logical task was to extend the derived expression to multi-phase windings, viz., star/delta connections and for any terminal condition of the neutral. Actually, it would be desirable to have a similar expression for open circuit natural frequency (OCNF) as well. A major highlight of this paper is that it presents a single, unified approach (using salient features of coefficients of the numerator and denominator polynomial of driving-point impedance) by which compact analytical expressions can be simultaneously derived for both SCNF and OCNF, for any multi-phase transformer configuration, and for any condition of the neutral terminal. Complete derivation details of the proposed method are presented, and then, the expressions for SCNF and OCNF are derived for 1- $\Phi$ isolated windings as well as 3- $\Phi$ (Y, $\Delta$ ) configurations. Finally, simulation results for all the cases are reported.

Analytical Expression for Resonances of an Inhomogeneous, Radial, Lossless LC Network

This paper is a sequel to the authors’ previous work wherein an analytical expression was derived for the harmonic sum of squares of natural frequencies of a lossless LC ladder network, which is a widely accepted means to model a single, isolated winding for analyzing impulse behavior. The present paper extends the previous result, so that it is applicable to multiple windings in actual transformers. The complexities of the previous work, viz., inhomogeneity and an exhaustive consideration of inductive coupling are retained, and additionally all possible capacitive couplings are now considered. Furthermore, the topology considered in this paper is generic enough to accommodate inductive branches emerging from any node. To the best of authors’ knowledge, there exists no compact closed-form expression to relate the natural frequencies to the inductances and capacitances for a network having this extent of arbitrariness in topology. The success of this method can be ascribed to careful inspection of the inductance matrix to identify hidden pattern and/or structure, followed by their deft manipulation guided by the basic law of mutual coupling between inductors. Interestingly, even a physical meaning can be assigned to each term of the derived expression, and this is done with the intention of assisting its use to conjure new applications.

Determination of transformer HV winding axial displacement extent using hyperbolic method – a feasibility study

In recent years, ultra-wideband (UWB) systems have been proposed for online monitoring of power transformers. This study aims at a new UWB-based method to determine the axial displacement (AD) extent in the transformer high-voltage (HV) winding. In the proposed design, two receiving antennas and one transmitting antenna are used. Two receiving antennas receive signals at two different positions due to axial displacement occurrence, and the displacement extent is determined using an analytical method known as hyperbolic method, which is based on signals time difference of arrival. The proposed method is initially studied by simulations using computer simulation technology software. Finally, the experimental results show the effectiveness of the proposed method to detect the AD extent in an actual transformer winding.

Feasibility study of waste vegetable oil as an alternative cooling medium in transformers

Vegetable oils due to their unique properties of availability and biodegradability can be considered as a reliable substitute for petroleum-based oils in transformer cooling system. Therefore, the performance of waste cooking vegetable oil after transesterification process for application in electrical transformers has been evaluated. The important properties of this oil such as density, heat capacity, viscosity, thermal conductivity, breakdown voltage and flash point have been measured and compared with those of mineral oil. Furthermore, the thermal behavior of the cooling system of an actual transformer was numerically simulated using the measured properties. Based on these measured data, the breakdown voltage and thermal conductivity of the vegetable oil as the two main indexes of transformer oil are, respectively, 48% and 33%, higher than those of the mineral oil, while its viscosity is considerably lower. Furthermore, the transformer hotspot temperature with vegetable oil is 3 °C lower than the mineral oil and the transformer experiences considerably lower temperature in the thermally critical region. Present study proposed the waste cooking vegetable oil not only as an alternative cooling medium for liquid-filled transformers but also as a sustainable way of using the waste resources, decreasing the environmental pollution and promoting environmental and economic benefits.

On the Optimality of Passive and Symmetric High-Frequency n-Terminal Transformer Models

This paper addresses the problem of obtaining optimal black-box models of n-terminal power transformers for transient studies. We use actual transformer data to demonstrate that a transformer model endowed with both passivity and symmetry can be optimally achieved only if the corresponding constraints are formulated and simultaneously included in the parameter estimation problem as opposed to enforcing them independently as two distinct post-processing model adjustments.

Research on mechanical fault diagnosis method of power transformer winding

Today, the accuracy of the fault mechanical diagnosis of transformer winding is low and the fault types cannot be judged, this study proposes a machine condition diagnosis method of transformer winding based on the combination of short-circuit reactance and mechanical vibration. During the process of diagnosis, first of all, from a power transformer's one and two side current and voltage, it can calculate the internal short-circuit reactance of the winding to judge the winding state. Then, it uses the wavelet transform to analyse the vibration signals of the transformer windings under different conditions and it uses the signal spectrum entropy as the input feature vector. Finally, using multi class support vector machine to train and test the feature vector, it realises the classification diagnosis of transformer winding in different states. By setting the actual different transformer winding faults of type S11-M-500/35, it gathers the corresponding parameter data and it tests the diagnosis method for the fault diagnosis of transformer winding verification. The diagnosis results are consistent with the actual fault, which verifies the validity and accuracy of the proposed method that is applied to the transformer winding fault diagnosis.

Classifying Transformer Winding Deformation Fault Types and Degrees Using FRA Based on Support Vector Machine

As an important part of power system, power transformer plays an irreplaceable role in the process of power transmission. Diagnosis of transformer’s failure is of significance to maintain its safe and stable operation. Frequency response analysis (FRA) has been widely accepted as an effective tool for winding deformation fault diagnosis, which is one of the common failures for power transformers. However, there is no standard and reliable code for FRA interpretation as so far. In this paper, support vector machine (SVM) is combined with FRA to diagnose transformer faults. Furthermore, advanced optimization algorithms are also applied to improve the performance of models. A series of winding fault emulating experiments were carried out on an actual model transformer, the key features are extracted from measured FRA data, and the diagnostic model is trained and obtained, to arrive at an outcome for classifying the fault types and degrees of winding deformation faults with satisfactory accuracy. The diagnostic results indicate that this method has potential to be an intelligent, standardized, accurate and powerful tool.

Equivalent Model Design and Test for Short Circuit Cumulative Effect of EHV Transformer

The actual 500kV transformer in operation is difficult to have short-circuit and research properties of the test conditions of the cumulative effect, transportation and multiple tests are expensive. It is of great engineering practical value to replace the original model with the real model which has the similar physical characteristics and mechanical vibration to do short-circuit and research tests. Firstly, under the condition of which the real model and the original model have the similar physical characteristics constant and the mechanical vibration, according to the relation of physical quantities, the equivalent criterion is deduced. Then, according to the equivalent criterion of the original transformer and the true model, a true model of 110kV transformer is designed. Secondly, the simulation software is used to verify the correctness of the equivalent and analyze the stress and mechanical vibration of the original model and the true model. Finally, many tests and researches have been carried out for the cumulative effect of short circuit.

A Novel Integrated Method to Diagnose Faults in Power Transformers

In a smart grid, many transformers are equipped for both power transmission and conversion. Because a stable operation of transformers is essential to maintain grid security, studying the fault diagnosis method of transformers can improve both fault detection and fault prevention. In this paper, a data-driven method, which uses a combination of Principal Component Analysis (PCA), Particle Swarm Optimization (PSO), and Support Vector Machines (SVM) to enable a better fault diagnosis of transformers, is proposed and investigated. PCA is used to reduce the dimension of transformer fault state data, and an improved PSO algorithm is used to obtain the optimal parameters for the SVM model. SVM, which is optimized using PSO, is used for the transformer-fault diagnosis. The diagnostic-results of the actual transformers confirm that the new method is effective. We also verified the importance of data richness with respect to the accuracy of the transformer-fault diagnosis.

Estimating the Equivalent Air-Cored Inductance of Transformer Winding From Measured FRA

A novel indirect measurement method to estimate the equivalent air-core inductance of an iron-cored transformer winding is proposed. The method utilizes frequency response analysis (FRA) magnitude data to estimate this quantity. Its implementation involves just two FRA measurements: one with the neutral end open circuited, whereas the other one is with a known external lumped capacitance connected between the neutral and ground. This equivalent inductance is straightforward to estimate from the short-circuit natural frequencies extracted from the two FRA magnitude plots. The recently derived analytical relationship connecting short-circuit natural frequencies to winding inductances and capacitances is employed for this purpose. Experimental demonstration is reported initially for actual windings with core removed to prove the feasibility of the method, and later, for an actual transformer. Finally, experiments on an air-cored winding are also reported to highlight one possible use of this quantity in discriminating radial and axial displacements.

Thermal management of a distribution transformer: An optimization study of the cooling system using CFD and response surface methodology

In this paper, a numerical scheme has been developed to examine the effective parameters on thermal management of distribution transformers and subsequently to optimize their cooling systems. In this regard, the response surface methodology (RSM) was used as the optimization method to minimize the hotspot temperature in the transformer as the response factor. A comprehensive three-dimensional computational scheme was employed considering the detailed geometrical specifications of an actual 200kVA distribution transformer to obtain the temperature field and the hotspot temperature. The accuracy of the numerical model was established via comparing the numerical results with the measured temperatures of a running transformer. The thermal variations of the thermo-physical properties of the transformer oil are determined experimentally and incorporated in the numerical modeling. A comprehensive parametric study among seven evidently effective parameters has been performed to identify the most effective parameters on the thermal performance of the transformer. It was found that fin height, length, and spacing are the more influential parameters among the examined parameters, which are also considered as the input variables in the optimization procedure. According to the RSM, the effects of the variations of these input variables in pre-specified ranges on the response, which is the hotspot temperature, are examined through the suggested runs by RSM. The results indicated that the hotspot temperature is more influenced by the fin height as compared to the fin length and spacing. Furthermore, the hotspot temperature decreases with the increase in fin height and length, while decreases as fin spacing increases. In addition, a correlation for the variations of the hotspot temperature as a function of the fin height (H), length (L), and spacing (S) is suggested using RSM. The significant finding is that the proposed optimum transformer configuration (H = 0.9 m, L = 0.08 m and S = 0.036 m) leads to the hotspot temperature reduction of about 16 °C as compared to the actual transformer geometry, which greatly affects the transformer life expectancy and safer performance.

Prediction Method for Power Transformer Running State Based on LSTM_DBN Network

It is of great significance to accurately get the running state of power transformers and timely detect the existence of potential transformer faults. This paper presents a prediction method of transformer running state based on LSTM_DBN network. Firstly, based on the trend of gas concentration in transformer oil, a long short-term memory (LSTM) model is established to predict the future characteristic gas concentration. Then, the accuracy and influencing factors of the LSTM model are analyzed with examples. The deep belief network (DBN) model is used to establish the transformer operation using the information in the transformer fault case library. The accuracy of state classification is higher than the support vector machine (SVM) and back-propagation neural network (BPNN). Finally, combined with the actual transformer data collected from the State Grid Corporation of China, the LSTM_DBN model is used to predict the transformer state. The results show that the method has higher prediction accuracy and can analyze potential faults.

Detection of moisture content in transformer oil using platinum coated on D-shaped optical fiber

The presence of moistures in transformer deteriorates transformer insulation. These effects decrease both electrical and mechanical strength of the transformer. Water in transformer oil also brings the risk of bubble formation when desorption of water increases the local concentration of gases in the oil. The water content in the insulating oil (or transformer oil) needs to be less than 10 ppm at normal temperature or contradictory, it will affect the efficiency of the power transformer system. Here, we report a D-shaped optical fiber sensor coated with a platinum thin layer with a thickness of 25 nm was designed to detect the response of transverse electric field (TE) power towards the content of moisture in the insulating oil. A Simulative based investigation using COMSOL Multiphysics has also been carried out to study the relation between analyte on the materials at different refractive index and the simulation study follows the finite element method (FEM). Four samples of aged oil were tested from actual transformer oil with different values of water contents of 15 ppm, 16 ppm, 18 ppm, and 21 ppm. The oil samples were dropped on the sensing region of the fiber and resulting in the drop of TE power from the initial value. It was observed that higher values of water percentages in the oil caused large fluctuations in TE power. On top of that, the changes in TE power show that the sensor is having fast response and good sensitivity.

Determination of transformer HV winding axial displacement occurrence, direction, and extent using time‐domain analysis of UWB signals

In this study, a new method is proposed to monitor axial displacement (AD) of transformer high-voltage (HV) winding using electromagnetic waves. The proposed method employed two receiving antennas and one transmitting antenna to exchange ultra-wideband (UWB) signals with the winding. The magnitude Euclidean distance (MED) index is used to compare the received signals when winding is sound or defective. Two receiving antennas receive signals at two different positions upon ADs in winding which causes different values in the amplitude of the received signals as well as the MED index of two receiving antennas. Hence, taking advantage of this feature, the occurrence, direction, and extent of AD can be identified. The proposed method is assessed using a simulation model. Then, experiments are conducted on an actual transformer winding using an experimental setup.

Characteristics of Negative Streamer Development in Ester Liquids and Mineral Oil in a Point-To-Sphere Electrode System with a Pressboard Barrier

This article presents the results of the studies on negative streamer propagation in a point-to-sphere electrode system with a pressboard barrier placed between them. The proposed electrode system gave the opportunity to assess the influence of the insulating barrier on streamer development in the conditions close to the actual transformer insulating system where the liquid gap is typically divided in parts by using pressboard barriers. The studies were performed for five commercial dielectric liquids. Among them two were biodegradable synthetic esters and two were biodegradable natural esters. Mineral oil, as the fifth liquid, was used for comparison. The measurements were based on electrical and optical experimental techniques. From the results obtained it may be concluded that, independently of the liquids tested, the electrical strength of the insulating system considered was increased by about 50%. In the case of streamer development assessed using photomultiplier-based light registration it is not possible to indicate clearly which of the liquids tested is better under the conditions of the experiment. In all cases streamers always developed slowly (2nd mode) at all voltage levels applied during the studies. In turn, the intensity of the discharge processes, comparing the same voltage levels, was mostly higher when streamers developed in ester liquids, however, the differences noticed were minimal.

Identification of Power Transformer Winding Mechanical Fault Types Based on Online IFRA by Support Vector Machine

A transformer is the most valuable and expensive property for power utility, thus ensuring its reliable operation is a major task for both operators and researchers. Online impulse frequency response analysis has proven to be a promising technique for detecting transformer internal winding mechanical deformation faults when a power transformer is in service. However, as so far, there is still no reliable standard code for frequency response signature interpretation and quantification. This paper tries to utilize a machine learning method, namely the support vector machine, to identify and classify the winding mechanical fault types, based on online impulse frequency response analysis. Actual transformer fault data from a specially manufactured model transformer are collected and analyzed. Two feature vectors are proposed and the diagnostic results are predicted. The diagnostic results indicate the satisfied classifying accuracy by the proposed method.