Transformer Windings Research Articles

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.

Transformer Winding Fault Classification and Condition Assessment Based on Random Forest Using FRA

At present, the condition assessment of transformer winding based on frequency response analysis (FRA) measurements demands skilled personnel. Despite many research efforts in the last decade, there is still no definitive methodology for the interpretation and condition assessment of transformer winding based on FRA results, and this is a major challenge for the industrial application of the FRA method. To overcome this challenge, this paper proposes a transformer condition assessment (TCA) algorithm, which is based on numerical indices, and a supervised machine learning technique to develop a method for the automatic interpretation of FRA results. For this purpose, random forest (RF) classifiers were developed for the first time to identify the condition of transformer winding and classify different faults in the transformer windings. Mainly, six common states of the transformer were classified in this research, i.e., healthy transformer, healthy transformer with saturated core, mechanically damaged winding, short-circuited winding, open-circuited winding, and repeatability issues. In this research, the data from 139 FRA measurements performed in more than 80 power transformers were used. The database belongs to the transformers having different ratings, sizes, designs, and manufacturers. The results reveal that the proposed TCA algorithm can effectively assess the transformer winding condition with up to 93% accuracy without much human intervention.

Transformer's frequency response analysis results interpretation using a novel cross entropy based methodology

Transformer defects can be identified by the FRA (frequency response analysis) that is a promising diagnostic technique. Despite the standardization in FRA measuring technique, its results interpretation is yet a research area. Because different faults types can be identified in various frequency bounds of the FRA signatures, it is necessary to identify the possible relationships between specific failures and frequency ranges in this contribution. For this purpose, a real transformer is used to conduct the essential tests, which include both healthy and faulted circumstances (axial displacement (AD), radial deformation (RD), and short-circuits (SC)). To identify efficient characteristics from the produced frequency response traces and improve interpretation accuracy of such traces, a new hyperbolic fuzzy cross entropy (FCE) measure is demonstrated and then utilized for the aim of discrimination and classification of transformer winding defects in pre-defined frequency ranges. After normalizing FRA results of the transformer under healthy and various fault circumstances the lower bounds from such responses have been extracted and then utilized to construct the desired form of the fuzzy sets of healthy and faulted circumstances. Then, a new hyperbolic FCE measure-based discrimination and classification of winding faults methodology is offered on the basis of highest and lowest FCE measure values. The highest FCE measure value between the fuzzy sets of healthy and faulted circumstances such as AD, RD and SC is designated to confirm the occurrence of winding faults in a suitable frequency range. The suggested methodology ensures smart interpretation of FRA signature and accurate classification of winding faults as it can effectively discriminate both healthy and faulted circumstances in the desired frequency ranges. The proposed approaches' performance is tested and compared by applying the experimental data after feature extraction.

Magnetic state balance technology of transformer based on magnetic field modulation strategy

The transformer core is easy to saturate in the half cycle under the influence of the remanent magnetism (RM) and the bias magnetism (BM), then the excitation surge current (ESC) and the DC bias will be generated, causing the transformer excitation current (TEC) distort, leading the winding temperature rise and decreasing the transformer insulation. In this paper, one kind of magnetic balance modulation method for the transformer core is proposed. TEC distortion could be improved by adjusting the transformer magnetic field distribution. Firstly, the AC/DC/DC converter was designed and connected to the auxiliary winding according to the hybrid transformer topology. Second, the specific modulated signal for the magnetic field modulation (MFM) was generated and output through the AC/DC/DC. The modulated forward and reverse DC current or the stepped AC current would be injected into the transformer winding to achieve the balance of the transformer magnetic state. Finally, in order to verify the correctness of the design scheme, a 1 kVA/380 V/220 V/38 V transformer experiment platform was built. The results showed that this proposed MFM strategy could effectively solve the impact of the transformer ESC, DC bias and prolong the transformer service life, which provides a novel idea to solve the transformer fault.

Research on Online Detection Method of Transformer Winding Deformation Based on VFTO Characteristics

At present, most of the winding fault detections of transformers use offline methods, which require the entire line to be powered off or after the transformer has been shut down due to a serious fault, and they cannot detect the running status of the windings in real time and online. Since the transformer will be impacted by VFTO during operation, the VFTO is used as the excitation, and the basic principle of the frequency response method is used to propose an online detection method of transformer winding deformation based on VFTO characteristics. The finite element software is used to calculate the equivalent circuit parameters of normal and deformed windings, and the equivalent circuit model of the transformer windings before and after deformation is established. Due to the uncertainty of the VFTO waveform, combined with the frequency response method, the VFTO waveform is injected into the transformer winding health, and the frequency response curve is obtained from the deformed equivalent circuit, which is used to analyze the change of the resonance point in the case of radial deformation, axial deformation, and axial displacement of the winding. The simulation results show that with VFTO as the excitation, the obtained resonance point change can comprehensively reflect the deformation information of the winding. At the same time, the feasibility of the method is verified by experiments.

Electromagnetic Vibration Characteristics of Inter-Turn Short Circuits in High Frequency Transformer

As a common fault of transformer winding, inter-turn short circuits cause severe consequences, such as excessive current and serious deformation of winding. Aiming to solve the problem of inter-turn short circuit at the end-winding and middle-winding of high frequency transformers (HFT), this paper considers the electromagnetic vibration characteristics of inter-turn short circuits (interleaved winding and continuous winding) at different positions, and the HFT is established by the multi-physical field coupling principle. Coupling equations for the inter-turn short circuit, as well as electromagnetic force and sound pressure level, are established to characterize the vibration noise mechanism of inter-turn short circuits. Furthermore, the HFT equivalent model is simulated in 3D finite element method (FEM) to emulate the real transformer operation and investigate the impact of interleaved winding and continuous winding under inter-turn short circuit faults. The short-circuit current and axial flux leakage, as well as the harmonic response of vibration acceleration and sound pressure level distribution, are obtained when inter-turn short circuits occur at different positions. Finally, the results show that the electromagnetic effect of the inter-turn short circuit in end-winding is worse than it is in middle-winding. Advantages in resisting impulse current make interleaved winding superior to continuous winding in terms of vibration and noise.

Equivalent Circuit Based Modeling of Multiple Winding Transformers

Developing suitable equivalent circuit models for multiple winding transformers provides great convenience in obtaining system equations. In general, circuits models are available for two-winding transformers. The paper proposes an equivalent circuit model based on ideal transformer representations consisting of dependent sources for multiple winding transformers. The use of equivalent circuit simplifies analysis and makes solutions more understandable. Since the model has a systematic structure, the increase in the number of windings does not affect the obtaining of the system equations. To validate the proposed equivalent circuit model, an application example, whose theoretical results can be easily seen, has been added to the study.

Determining Accuracy of Temperature Limit Change in Power Transformer Core Using Temperature-Time Parameter Method

The efficient transmission of electrical energy depends on amplifying voltage values with power transformers. To obtain higher efficiency from transformers, the core and winding type of transformer, the geometric structure of the core, and the shaping techniques in the windings are changed. This requires modeling transformer windings with equivalent circuits and calculating the inductance and electrical parameters appropriately. In this study, two-dimensional (2D) finite element solutions with energy perturbation and flux-coupling methods are used. The correctness of the inductance values of transformer windings was established, and the design was performed, by considering the inductance and electrical parameter values, which are comparable to the energy perturbation and flux connection. However, when two-dimensional calculated fields are used, the flux coupling method requires less computation and gives numerically more accurate results than the energy perturbation method. So, it is concluded that the flux-coupling approach should be chosen as the preferred method for calculating the inductance and electrical parameters of transformer windings. The numerical properties and equivalence of energy perturbation and flux-connection methods, the “apparent” inductance value of the primary and secondary field windings of power transformer operating under transient conditions, using the temperature-time parameter method, are calculated and its accuracy is demonstrated.

Study on Vibration Characteristics of Transformer Winding

Compared with the existing winding deformation detection technologies, such as the frequency response method and short-circuit reactance, the vibration analysis method can effectively detect the loose state of windings. This paper has carried out mechanism analysis and experimental study on the change of winding modal characteristics caused by two kinds of defects, analyzed the transmission characteristics of three-phase double winding transformer winding vibration in the transformer oil and structure, studied the influence of pad falling off, plastic deformation and other defects on the mechanical state of the winding, calculated the winding short-circuit vibration signals corresponding to different mechanical states, and extracted the vibration characteristics that can effectively reflect the mechanical state of the winding. The research conclusion can provide an important basis for transformer fault diagnosis.

Optimal Dielectric Design of Medium Voltage Toroidal Transformer With Electrostatic Shield Under Fast Front Excitation

Accurate calculation of transient overvoltages and dielectric stresses from fast-front excitations is required to obtain an optimal dielectric design of power components subjected to these conditions, which are commonly due to switching and lightning, as well as utilization of power-electronic devices. Toroidal transformers are generally used at the low voltage level. However, recent investigations and developments have explored their use at the medium voltage level. This paper analyzes the model-based improvement of the insulation design of medium voltage toroidal transformers. Lumped and distributed parameter models are used and compared to predict the transient response and dielectric stress along the transformer winding. The parameters of the toroidal transformer are computed using the finite element method considering a three-dimensional geometry. Different strategies for insulation design are proposed by means of optimal insulation thickness and electrostatic shield to reduce transient overvoltage and dielectric stress. The results show that the proposed optimal insulation design based on particle swarm optimization with electrostatic shield can substantially reduce the dielectric stress and dielectric distances. Comparison between simulations and experimental results demonstrates that the frequency domain modeling approach results in accurate calculation of transient overvoltages produced by fast front excitation and can be used effectively for insulation design.

The Effects of PWM With High dv/dt on Partial Discharge and Lifetime of Medium-Frequency Transformer for Medium-Voltage (MV) Solid State Transformer Applications

Medium-frequency (MF) transformer in a phase-shift modulated dc solid state transformer (SST) is prone to partial discharge (PD) that impacts the system reliability and lifetime. Tightly packed MF transformer windings carrying PWM voltages create favorable conditions for PD inception. A peak potential condition is created between adjacent posterior windings as a result of phase-shifted modulation. This along with fast alternating electric fields incepts PD at lower than expected operating voltages. Early inception of PD lead to premature transformer failure leading to unanticipated DC SST down-time. The effects of PWM voltages containing high dv/dt switching transients on PD and lifetime characteristics of MF transformer in a dc SST is not yet understood, which is investigated in this paper. A non-intrusive PD detection strategy for MF PWM ac voltage is presented using high speed optical sensors. PD characterization is performed on Kapton polyimide insulated copper foil windings for a foil-type MF transformer. Winding samples are stress tested with steady state PWM voltages upto 2 kV and frequencies upto 50 kHz with high dv/dt upto 60 V/ns while maintaining the transformers geometric profile. Accelerated dielectric lifetime characterization is performed and novel lifetime prediction models are derived containing both frequency and dv/dt dependent variables.

Forced Air-Cooling Thermal Design Methodology for High-Density, High-Frequency, and High-Power Planar Transformers in 1U Applications

Due to increased loss per unit volume in power transformers when operating at higher frequency, the increase in cooling system size can outweigh high-frequency transformer (HFT) size reduction benefits. Conventional air-cooling approach simply adopts oversized cooling fans with high airflow to keep the transformer below a temperature limit, resulting in a large footprint and high power consumption. For many applications using air cooling, more challenges arise when multiple transformers are placed in a dimension-constrained space in which free airflow from the cooling system is easily disrupted. This work seeks to address this tradeoff by presenting a high-density, low-profile, forced air-cooling system for HFTs. The combination of an epoxy resin cast transformer winding and converging air duct is proposed to minimize the heat transfer barrier from both the internal and external structures of the high-frequency power transformer. The air-cooling system design process is demonstrated with a 15-kW load test featuring two 500-kHz planar Litz-wire transformers. The proposed transformer cooling system achieves a power density of 635 W/in3, a peak height of 43 mm, and a cooling power consumption of 6.8 W. Compared to using a 120 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times120$ </tex-math></inline-formula> mm cooling fan, peak winding temperature is reduced to 8%, the cooling system volume is reduced to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3\times $ </tex-math></inline-formula> , and a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4\times $ </tex-math></inline-formula> reduction of cooling power consumption is achieved.

A New Procedure for High Frequency Decentralized Modeling Parameters Identification of a Transformer Winding Construction Using Frequency Response Analysis Based on Logistic Chaotic JAYA Algorithm

A New Procedure for High Frequency Decentralized Modeling Parameters Identification of a Transformer Winding Construction Using Frequency Response Analysis Based on Logistic Chaotic JAYA Algorithm

Radial stability evaluation and cumulative test of transformer windings under short-circuit condition

Radial stability evaluation and cumulative test of transformer windings under short-circuit condition

Effect of Test Cable Termination on Frequency Response of Transformer Winding

Sweep Frequency Response Analysis (SFRA) method is the most powerful tool to predict the condition of transformer winding. The reliable measurement of frequency response is equally important as its interpretation. A few standards (IEEE std. C57.149-2012, IEC 60076, the Chinese Electrical Power Industry Standard ICS27.100.F24-2005) &amp; much research work have been published, stating dos &amp; don’ts while measuring the frequency response of transformer winding. In this paper, an attempt is made to introduce an additional factor affecting frequency response, while doing measurements. Here, the effect of test cable termination at transformer winding terminals, to prevent signal reflection, on frequency response is presented. A possible way to select suitable value/s of terminating resistance that can correct frequency response is also proposed.

Fault diagnosis of transformer winding short circuit based on WKPCA-WM and IPOA-CNN

When the winding of the power transformer is short-circuited, the winding will experience constant vibration, which will cause axial instability of the winding, and then lead to winding looseness, deformation, bulge, etc., therefore, a diagnosis method based on the Improved Pelican Optimization Algorithm and Convolutional Neural Network (IPOA-CNN) for short-circuit voiceprint signal of transformer windings is proposed. At the same time, considering the input parameter dimension of deep learning cannot be too high, a new feature parameter selection method is constructed for this model. Firstly, the frequency characteristics of winding acoustic vibration signals are analyzed, and then the characteristic parameters of transformer acoustic signals are extracted by Wavelet Packet Energy Spectrum (WPES) and Mel Frequency Cepstrum Coefficient (MFCC), respectively. Then, the two methods are combined to construct the WM feature extraction algorithm, and the Weighted Kernel Principal Component Analysis (WKPCA) is used to reduce the dimension of the feature to obtain the feature parameters with accurate feature information and low redundancy; Finally, combined with Sobol sequence to optimize the initial population of Pelican Optimization Algorithm (POA), the convolution kernel of Convolutional neural network (CNN) was optimized by IPOA, and the optimal convolution kernel was obtained. The transformer winding short-circuits voiceprint diagnosis models of WKPCA-WM and IPOA-CNN were constructed, which realized the accurate diagnosis of winding short-circuit voiceprint. The validity and feasibility of the method are verified by the acoustic signal data collected in the laboratory.

Calculation of inlet capacitance for long-duration induction voltage test of single-phase three-winding converter transformers

The converter transformer is one of the core equipment in the high-voltage DC (HVDC) transmission project. The capacity of the converter transformer is much larger than that of an ordinary AC transformer, and its main function is to convert the AC system voltage to the phase change voltage required by the converter. The long-duration induction voltage test is an important technical means to assess the insulation strength of electrical equipment, and the calculation of the inlet capacitance of the converter transformer in the test design is extremely critical. This paper conducts circuit and mathematical modeling based on the structure of a single-phase three-winding converter transformer, calculates the equivalent capacitance between each winding of the converter transformer and each winding to ground by the model, and uses each equivalent capacitance to calculate the voltage added inlet capacitance, then obtains the appropriate compensation inductance. Moreover, the calculated inlet capacitance is verified by using the field test data, and the verification results show the reasonableness of the model. Finally, the calculation results are analyzed for errors and possible sources of errors are pointed out. This inlet capacitance calculation method has some universality and is expected to be promoted and applied in this field.

Fast calculation of temperature distribution in oil-immersed transformer windings based on U-net neural network

In this paper, a fast computational method based on the training of the U-net neural network is proposed to solve the fluid-thermal coupling problem of transformers. First, the input variables are selected according to the fluid-thermal coupling principle, and the finite volume method is applied to obtain the output results under different operating conditions and make them into training sets and test sets. Second, the training sets are normalized and input into the U-net neural network. At the same time, three hyperparameters that have more influence on the network training are discussed in detail, and the optimal combination of hyperparameters is determined. Finally, the prediction set is fed into the trained model for prediction computation, and the results are subjected to the inverse normalization operation, whose predictive results are consistent with those calculated by the finite volume method. In addition, the computational time is shortened from 300 to 0.07 s, and the prediction variance does not exceed 0.055 K2. The results show that the proposed method can be used to obtain the temperature of immersed transformer windings quickly, which provides an effective tool for real-time temperature simulation of the digital twin of power transformers.

A three‐level three port isolated converter with reduced current stress for DC microgrid applications

SummaryThis paper proposes a three‐level three port isolated converter (3L3PIC), which can be employed as an intermediate power conversion circuit for connecting different DC bus voltages in a DC microgrid. This topology utilize half bridge multilevel structure to reduce voltage stress across the transformer windings and the semiconductor switches. Conventionally the power transfer between the ports of a 3PIC were attained by traditional phase‐shift modulation (TPM), but this will impose increased current stress and associated losses in the converter at wide change in voltage conversion ratio. To minimize these losses, this paper introduces a 3L3PIC, that is, by employing dual phase‐shift modulation (DPM) in 3PIC. Steady state analysis of 3L3PIC are presented and derived the power transfer equations between the ports. The current equations through each port are determined at different combinations of voltage conversion ratios. Procedure for obtaining optimized phase‐shift values for both TPM and DPM techniques in 3PIC are explained. A comparison between the modulation schemes in 3PIC is performed and found better results for the DPM technique in terms of reduced current stress, reduced circulating power flow, and extended soft switching region. This in turn leads to a reduction in conduction losses and transformer losses in the converter. A hardware prototype of 1.5 kW 3PIC has been implemented and tested. The experimental results obtained validates with the theoretical analysis.

Research on Mechanical Properties of Winding Axial Bending Under Unbalance of Transformer Pad

To improve the study on the influence of transformer windings and pad support on transformer short-circuit resistance, the calculation method of wire bending elastic modulus is analyzed, and the sample test is carried out: The influences of the unbalance of the two ends of the wire between the number of wires wound and the span of adjacent pads on the force-deflection curve, the bending force at the selected deflection, and the elastic modulus of bending were analyzed. The results showed that: Increasing the number of wires and decreasing the height difference of adjacent pads can improve the bending force and bending elastic modulus of wires, the axial stability, and short-circuit resistance of transformer windings. When the height of the adjacent pad is not balanced, the axial force can increase the compression degree between the pad and the wire, and reduce the span of the wire. Under the action of force, the wire yields twice, which further reduces the bending force and elastic modulus of the wire. This research can provide test data support for improving the installation of transformer winding pads and theoretical evaluation of short-circuit tolerance.