Transformer Windings Research Articles

Correlation-based polarity-check algorithm for instrument transformers

A polarity identification is very important for operation of transformers, measurement and protection equipment, where it is useful in analyzing of transformer connections and operation as well as testing of protective systems. Moreover, it’s essential in assessment of power systems performance during both normal and abnormal operation. Ensuring the correct polarity of the primary and secondary windings in voltage and current transformers is of paramount importance for various measurement and protection schemes in power networks. This paper proposes a digital polarity detector and tester using correlation coefficients and nine polarity indices calculated for instrument transformer signals. In order to test the performance of the proposed polarity tester algorithm, MATLAB code is imported to the LABVIEW model, and the numerical data obtained from the synchronous generator terminals via instrument transformers are interfaced with the computer through the Data Acquisition Card (DAC). The experimental system consists of a motor-generator set supplying a three-phase inductive load with instrument transformers connected to measure each phase voltage and current. The obtained results for various operating conditions and different types of abnormal conditions prove that the suggested algorithm is accurate, reliable and applicable to smart grids and substation automation systems. It can be considered as an integrated system incorporated with digital fault recorders, relays and meters.

Optimized Design of Full‐Bridge LLC Planar Transformer Based on Variable‐Width Windings

ABSTRACTTo address the issue of significant loss increase in planar transformers at high frequencies in LLC resonant converters, the winding width of the transformer was optimized. This design minimizes losses due to eddy currents and skin effects, thereby optimizing the transmission efficiency of the LLC resonant converter. This paper developed a mathematical model of the transformer windings, analyzed the losses in the windings and the core of the planar transformer, and summarized the design rules for three commonly used winding geometries. By determining the optimal winding width, the transformer losses were optimized. Using the finite element simulation software Maxwell3D, a 3D simulation model of the transformer was constructed. The simulation results were compared, and a 500‐W full‐bridge LLC prototype was built to validate the principles summarized in the paper.

Algorithm for sequences exploration and optimization of a Multi-Active-Bridge

This paper focuses on the control of an n-port Multi-Active Bridge, providing insights into switching sequences, a time-domain model, and an optimization algorithm concerning conduction and switching losses. Central to this analysis is the introduction of a novel concept known as winding voltage sequences, which encapsulate the switching sequences employed by the converter bridges. The algorithm proposed in this article aims to derive analytical expressions for the currents flowing through all transformer windings (and switches) for each switching sequence. This control methodology is characterized by a set of parameters—inter-leg and inter-bridge phase shifts—whose diverse values are systematically explored to attain an optimal solution.

A Novel Transformer Winding Design Strategy for Efficiency Improvement and Harmonic Sup-Pression in Industrial Power System

A Novel Transformer Winding Design Strategy for Efficiency Improvement and Harmonic Sup-Pression in Industrial Power System

Numerical and Experimental Investigations on Transformer Winding Damages Under Multiple Short-Circuit Faults

Numerical and Experimental Investigations on Transformer Winding Damages Under Multiple Short-Circuit Faults

New approach for accurate discrimination and location of power transformers with different internal winding faults.

Power transformers are essential elements in power systems and thus their protection schemes have critical importance. In this paper, a scheme is proposed for accurate discrimination and location of internal faults in power transformers using conventional measuring devices attached to the transformer. Different types of internal winding faults are intensely considered: partial discharge, inter-disk faults, series and shunt short circuit faults and axial displacement. Depending on the transformer measured output voltage, input voltage and the input current, the construction of a locus diagram (ΔV-Iin) serves as an indicator for any physical modification to the winding. Using five suggested features extracted from the developed locus, an artificial neural network (ANN) technique is applied to accurately distinguish any deviation from the transformer healthy condition. The exact location of each fault inside the windings of power transformer is then determined. The obtained results validate the usefulness of the proposed scheme for different internal faults. The superiority of the proposed scheme is extensively examined by comparing its results with some published schemes.

Adsorption and gas sensing properties of Cun, Agn and Rhn (n=1–3) clusters doped with WTe2 for transformer winding deformation fault gases

In order to solve the problem that the initial WTe2 has poor adsorption effect on transformer winding deformation fault gas, this paper uses density functional theory (DFT) to study the adsorption behavior of three target gases (CO, C2H2 and CO2) on the surface of WTe2 substrate doped with three metal clusters: Cun, Agn, and Rhn (n=1–3). By analyzing the adsorption distance, adsorption energy, DCD and DOS of the three systems, the effect of metal cluster doping on the adsorption of fault gas by WTe2 was revealed. The results show that metal cluster doping can effectively improve the conductivity of WTe2 substrate and make its band structure more compact. CO and C2H2 have good adsorption characteristics in the three doping systems, while CO2 can be effectively adsorbed by Rh cluster-doped WTe2. In addition, this article also uses work function and band gap to analyze the effect of gas adsorption on substrate conductivity, and discusses the practical application prospects of the three metal cluster doping systems from the perspectives of recovery time and sensitivity, and achieved good results. This paper provides theoretical guidance for exploring the application prospects of WTe2 substrate in transformer winding deformation fault diagnosis and gas detection.

Effect of SF6 circuit breaker parameters on switching overvoltages evaluated based on nominal modes of converter transformers

In this work, we set out to investigate the influence of operating currents of SF6 circuit breakers on the magnitude of overvoltages during switching of converter transformers. The experience of electrical equipment operation is analyzed with a focus on the problems associated with the natural aging of insulation, overloads, and switching overvoltages. The methods of equipment diagnostics were used. According to statistical data, at present, about 37% of short circuits between phases and 42% of single-phase earth faults in electrical networks of industrial enterprises occur due to switching overvoltages. The conducted tests showed that the overvoltages emerging during switching by SF6 circuit breakers of converter transformers, which are used in aluminum smelters, may reach a three-fold rated voltage of the network. This threatens the insulation of transformer windings, cable line, and the switch itself. It was established that an increase in operating currents of an LF2 circuit breaker, not exceeding 27.8% of the rated current of the switch, leads to an increase in overvoltages during switching of converter transformers. At a further increase in the operating currents of the circuit breaker by more than 27.8% of the rated current of the circuit breaker, a sharp decrease in the value of switching overvoltages is observed. Therefore, the operating currents of SF6 circuit breakers were established to affect the level of switching overvoltages of converter transformers. The underlying mechanism of this phenomenon was determined, which should be taken into account when improving the reliability of power supply of converter transformers and, consequently, the reliability of aluminum production. The feasibly of resistive-capacitive dampers as the most effective means for limiting overvoltages during switching of converter transformers was confirmed.

Evaluating the Harmonic Effects on the Thermal Performance of a Power Transformer

Harmonics in the power grid contribute to increased power losses in both the core and windings of power transformers. These losses lead to abnormal rises in temperature causing overheating and reduce the efficiency of the transformer. If the losses and temperature exceed the values set during the design stage for linear load conditions, it can damage the transformer’s insulating materials and shorten its lifespan. To assess the thermal impact of power system harmonics on transformers under steady-state and transient conditions, the rated losses and harmonic losses of the transformer are calculated. These losses are then inputted into a developed thermal 3D finite element method (FEM) performance model to determine the temperature distribution of transformer components. The numerical results from the thermal model will be compared with data from a Hyundai test report and real measurements from Egypt’s Kureimat power plant, specifically a 750 MW combined cycle power plant. The thermal modeling is focused on a step-up (16.5/240 kV), 240 ± 4 × 2.5%, 180/240/300 MVA power transformer operating in ONAN, ONAF1, and ONAF2 modes. This paper shows that the developed model aligns closely with actual measurements and the HYUNDAI test report. The loss calculations reveal that the discrepancy in total losses, with and without accounting for harmonics, becomes more pronounced as the load increases. Using this model, the presence of grid harmonics results in a higher temperature distribution across transformer components, leading to an increase in the hot spot temperature.

Simulation and experimental analysis of dynamic thermal rise relaxation characteristics for dry-type distribution transformer

Abstract The temperature distribution characteristics of dry-type distribution transformers reflect their overall performance and quality. Distribution transformer daily load changes dramatically, its temperature fluctuates within a certain range. However, most of the research results on transformer temperature rise focus on the steady-state temperature characteristics of transformers, and lack of research related to dynamic temperature rise characteristics. This paper carries out a multi-physics coupling simulation and experimental verification of the dynamic temperature rise relaxation characteristics. The simulation uses the “electromagnetic-flow-thermal” multi-physics coupling analysis method to simulate the steady-state temperature rise characteristics and dynamic temperature rise relaxation characteristics of windings under different load rates. Then, this paper also explores the correlation between the dynamic temperature rise relaxation characteristics and load rate at the typical positions of high-voltage windings and low-voltage windings. The results show that the temperature rise of the winding shows the law of increasing the saturation index function with the increase of the load application time at any load rate. A quantitative characterization model of dynamic temperature rise relaxation behavior at different positions of transformer windings is constructed. It is found that the steady-state temperature rise value of different parts of the winding increases regularly as a power function with the increase of load rate, while the constant value of dynamic temperature rise relaxation time in different parts of the winding decreases as a power function with the increase of load rate. The verification results of the quantitative characterization model of dynamic temperature rise relaxation behavior show that the maximum error of the measured and theoretical steady-state temperature rise value is only 1.56 K, and the maximum error of the constant value of dynamic temperature rise relaxation time is only 0.082 h. These findings provide valuable insights into the performance and quality of dry-type distribution transformers, and can help improve their design and operation for better efficiency and safety.

A new approach towards more accurate modeling of mechanical defects in power transformer windings

In many cases, power transformers can continue their normal operation despite mechanical defects in their windings. However, estimating the lifespan and assessing the risk of using a transformer with mechanical defects depend on detailed studies of insulation aging and the distribution of transient voltages along the winding, and consequently, the likelihood of partial discharge. Risk assessment studies can only be effectively conducted through accurate modeling of transformers across a wide frequency range. In this study, an attempt has been made to investigate the impact of winding mechanical defects on the transformer equivalent circuits parameters using finite element method precisely modeling of transformer windings, without applying approximation or common simplifications. To compare the effect of each mechanical defect on the resistance, inductance, and capacitance matrices arrays, an index called fault classification accuracy has been used. The investigations have shown that the capacitance matrix arrays undergo the most significant changes for all types of modeled defects in this research. To examine the impact of defects on the transformer frequency response, a π coupled model that directly uses output matrices of finite element modeling has been employed. The sensitivity of various components of frequency response has also been investigated for the used model.

A transformer winding and core mechanical fault diagnosis approach based on VMD-MFE and GWO-MKELM

A transformer winding and core mechanical fault diagnosis approach based on VMD-MFE and GWO-MKELM

Study on temperature characteristics of inter-turn short circuit in oil-immersed self-cooling transformer windings

Study on temperature characteristics of inter-turn short circuit in oil-immersed self-cooling transformer windings

Axial vibration characteristics analysis of transformer windings based on magnetic‐structural coupling correction model

AbstractDue to the strong coupling effect between the internal magnetic field and the structural field of the transformer, the magnetic‐structural coupling should be considered in axial vibration process of the winding short‐circuit impact. A 110 kV transformer is taken as the research object. Firstly, the vibration modal characteristics of the transformer are calculated using the classical axial vibration model, and the spatial distribution of the leakage magnetic flux density of the iron core window is obtained based on the image method, which is used as the basis for calculating the excitation electromagnetic force. With the consideration of the non‐linear mechanical characteristic of the pad, the dynamic stiffness equation is analysed and established and the magnetic‐structural coupling correction model is constructed. Finally, the winding vibration amplitudes obtained respectively by the classical model, the magnetic‐structural coupling model, and the magnetic‐structural coupling correction model considering the dynamic stiffness are compared. The results show that, compared with the classical model, the vibration amplitude increment with the magnetic‐structural coupling correction model is less. The dynamic stiffness will hinder the vibration intensification. The magnetic‐structural coupling correction model can provide a more accurate calculation scheme for the winding vibration characteristic analysis.

Electromagnetic–Structural Finite Element Analysis of Copper and Aluminum Windings in Power Transformers under Short-Circuit Conditions

Electromagnetic forces can lead to the structural failure of power transformers due to extreme loading conditions, vibration, and/or fatigue. Therefore, studying the nature and the magnitude of these forces is a key task in the design and failure analysis of such important equipment. Keeping this issue in mind, this work aims at conducting a numerical analysis in order to evaluate the mechanical stresses and displacements of windings in power transformers due to the action of electromagnetic forces. With this purpose, a finite element model is developed considering electromagnetic and mechanical effects assuming short-circuit conditions. The study compares the cases employing copper and aluminum windings with header tap, in different temperatures. The model developed in this work is verified against analytical solutions. The numerical calculations allow for performing a detailed analysis in terms of the distribution of both displacements and stresses along the windings, which is of great relevance for identifying critical structural points and avoiding structural failure. Overall, the obtained results demonstrate that the finite element model is a useful tool for the structural design of power transformers that allow for investigating and optimizing key aspects before manufacturing.

A Novel Methodology for the Transformer Winding Equivalent Ladder Network Circuit Parameters Identification by Employing the Frequency-Domain and Population Based Method

A Novel Methodology for the Transformer Winding Equivalent Ladder Network Circuit Parameters Identification by Employing the Frequency-Domain and Population Based Method

Study on the Effect of Multi-Gap Arrester Truncation on the Overvoltage of Lightning Intrusion Wave

Lightning protection near the fan is the key point of lightning protection in wind farm, which affects the safe and effective delivery of wind power resources. At present, the three-phase multi-gap arrester installed on a base tower behind the collector can cooperate with the zinc oxide arrester to reduce the system failure caused by the arrester failure. However, the chopped wave generated by the multi-gap arrester when it acts is transmitted to the fan box transformer along the line, which may threaten the insulation of the transformer winding. Based on the above problems, this paper builds a simulation model on ATP to analyze the impact of wave clipping of multi-gap arrester on the insulation of fan transformer windings, considers the conventional installation mode and the limit installation mode of multi-gap arrester, and calculates that the wave clipping overvoltage generated by multi-gap arrester after being struck by lightning in two cases is the impact on the insulation of fan transformer. Through the simulation analysis, it is found that the higher the amplitude of the lightning current, the larger the amplitude of the overvoltage generated by the truncated wave, the steeper the wave head, and the greater the threat to the insulation of the fan box. The damage degree of round lightning is less than that of counter lightning. When a multi-gap arrester is installed in a collector tower, the 100[Formula: see text]kA lightning current may destroy the insulation of the fan box transformer winding and require additional protective measures. It is recommended that the multi-gap arrester be installed from the next pole tower of the collector tower in the wind farm.

Inversion Method for Transformer Winding Hot Spot Temperature Based on Gated Recurrent Unit and Self-Attention and Temperature Lag.

The hot spot temperature of transformer windings is an important indicator for measuring insulation performance, and its accurate inversion is crucial to ensure the timely and accurate fault prediction of transformers. However, existing studies mostly directly input obtained experimental or operational data into networks to construct data-driven models, without considering the lag between temperatures, which may lead to the insufficient accuracy of the inversion model. In this paper, a method for inverting the hot spot temperature of transformer windings based on the SA-GRU model is proposed. Firstly, temperature rise experiments are designed to collect the temperatures of the entire side and top of the transformer tank, top oil temperature, ambient temperature, the cooling inlet and outlet temperatures, and winding hot spot temperature. Secondly, experimental data are integrated, considering the lag of the data, to obtain candidate input feature parameters. Then, a feature selection algorithm based on mutual information (MI) is used to analyze the correlation of the data and construct the optimal feature subset to ensure the maximum information gain. Finally, Self-Attention (SA) is applied to optimize the Gate Recurrent Unit (GRU) network, establishing the GRU-SA model to perceive the potential patterns between output feature parameters and input feature parameters, achieving the precise inversion of the hot spot temperature of the transformer windings. The experimental results show that considering the lag of the data can more accurately invert the hot spot temperature of the windings. The inversion method proposed in this paper can reduce redundant input features, lower the complexity of the model, accurately invert the changing trend of the hot spot temperature, and achieve higher inversion accuracy than other classical models, thereby obtaining better inversion results.

Dependability Analysis of the Negative-Sequence Turn-to-Turn Fault Protection Schemes for MMC-HVDC Converter Transformers

This paper addresses two complex areas of research: the detection of turn-to-turn faults (TTF) in power transformers and the impact of inverter-based resources on the TTF protection scheme operation. Detecting turn-to-turn faults in power transformers by protection algorithms poses a challenge due to the minimal fault currents observed at transformer terminals. Yet, the demand for dependable TTF protection is very high because of the high fault currents inside the shorted turns and the resulting damage consequences. On the other hand, for such sensitive protection, adverse conditions such as transformer inrush currents or CT errors may lead to protection maloperation. Moreover, the fault current characteristic of the inverter-based source infeed is very different compared to the synchronous machine infeed, particularly concerning the negative-sequence current used in the TTF protection schemes, which calls for thorough research analysis. A simulation model of the converter transformer capable of simulating TTFs, and the Modular Multilevel Converter (MMC) for a High Voltage Direct Current (HVDC) transmission link, has been developed. The test results of turn-to-turn fault protection schemes in inverter-based generation-dominated power systems compared to the synchronous generator infeed are presented. The negative-sequence current protection quantities are analysed in more detail for TTFs with small and large number of shorted turns, i.e. without and with reactive negative-sequence current injection by the MMC control. Finally, the paper assesses the dependability of the transformer differential protection and sensitive TTF protection schemes in detecting faults with different numbers of shorted turns and fault resistance for TTFs occurring in the star and delta winding of the converter transformer.

Localization for Dual Partial Discharge Sources in Transformer Oil Using Pressure-Balanced Fiber-Optic Ultrasonic Sensor Array.

The power transformer is one of the most crucial pieces of high-voltage equipment in the power system, and its stable operation is crucial to the reliability of power transmission. Partial discharge (PD) is a key factor leading to the degradation and failure of the insulation performance of power transformers. Therefore, online monitoring of partial discharge can not only obtain real-time information on the operating status of the equipment but also effectively predict the remaining service life of the transformer. Meanwhile, accurate localization of partial discharge sources can assist maintenance personnel in developing more precise and efficient maintenance plans, ensuring the stable operation of the power system. Dual partial discharge sources in transformer oil represent a more complex fault type, and piezoelectric transducers installed outside the transformer oil tank often fail to accurately capture such discharge waveforms. Additionally, the sensitivity of the built-in F-P sensors can decrease when installed deep within the oil tank due to the influence of oil pressure on its sensing diaphragm, resulting in an inability to accurately detect dual partial discharge sources in transformer oil. To address the impact of oil pressure on sensor sensitivity and achieve the detection of dual partial discharge sources under high-voltage conditions in transformers, this paper proposes an optical fiber ultrasonic sensor with a pressure-balancing structure. This sensor can adapt to changes in oil pressure environments inside transformers, has strong electromagnetic interference resistance, and can be installed deep within the oil tank to detect dual partial discharge sources. In this study, a dual PD detection system based on this sensor array is developed, employing a cross-positioning algorithm to achieve detection and localization of dual partial discharge sources in transformer oil. When applied to a 35 kV single-phase transformer for dual partial discharge source detection in different regions, the sensor array exhibits good sensitivity under high oil pressure conditions, enabling the detection and localization of dual partial discharge sources in oil and winding interturn without obstruction. For fault regions with obstructions, such as within the oil channel of the transformer winding, the sensor exhibits the capability to detect the discharge waveform stemming from dual partial discharge sources. Overall, the sensor demonstrates good sensitivity and directional clarity, providing effective detection of dual PD sources generated inside transformers.