• Energy Research

The power transformer is important equipment for energy conversion and transmission in the power grid and its failure will bring significant economic losses to the power system. The hot-spot temperature is a primary factor affecting the reliability and service life of power transformers. In order to calculate the temperature distribution of oil-immersed transformer windings accurately, it is required to solve a multi-physical problem, in which the magnetic field and the fluid-temperature field are coupled. In the simulation of multi-physical field of transformer, many studies usually omit the turn-to-turn insulation of windings to simplify the oil-immersed transformer model. The purpose of this paper is to investigate the effect of the turn-to-turn insulation of windings in oil-immersed transformers on the simulation results. First, a 2D axisymmetric transformer model was established in ANSYS to study the effect of low-voltage winding turn-to-turn insulation on the magnetic field simulation results. The differences of eddy current losses in the simulation were also calculated in terms of the magnetic field simulation results. It is found that the turn-to-turn insulation does not affect the magnetic field distribution in evidence from the simulation results. Besides, the values of the magnetic field and eddy current loss appear significant differences only at both ends of the low-voltage winding. Second, the fluid-temperature field of the transformer was solved in Fluent and the turn-to-turn insulation was the controlled objective in the solution process with consideration of the difference in winding losses. The simulation results show that the turn-to-turn insulation of the winding does not change the oil flow distribution in simulation. The simulation model with turn-to-turn insulation appears a gradient in the temperature distribution of the discs and a rise in the overall temperature distribution. Moreover, this paper analyzes the possible reasons for the differences in the simulation results of the magnetic and temperature fields caused by the turn-to-turn insulation. Some results and conclusions in this paper can be used in related studies and designs.

A finite element method, which directly uses the node electric scalar potentials and node charge densities as variables, is used to predict the electric field and charge density distributions under polarity reversal (PR) voltage. The penalty method is adopted to impose the Dirichlet boundary values and the Crank-Nicolson (C-N) algorithm is then used to solve the transient equation. The surface node charge densities on the perfectly conducting boundaries are adopted to accurately obtain the normal electric field strengths. The method is tested by a two layer coaxial model and applied to analyze the linear and nonlinear transient electric fields and boundary charge densities of a ±500 kV converter transformer under PR voltage.

In order to study the coupling fluid and thermal problems of the local winding in oil-immersed power transformers, the least-squares finite element method (LSFEM) and upwind finite element method (UFEM) are adopted, respectively, to calculate the fluid and thermal field in the oil duct. When solving the coupling problem by sequential iterations, the effect of temperature on the material property and the loss density of the windings should be taken into account. In order to improve the computation efficiency for the coupling fields, an algorithm, which adopts two techniques, the dimensionless LSFEM and the combination of Jacobi preconditioned conjugate gradient method (JPCGM) and the two-side equilibration method (TSEM), is proposed in this paper. To validate the efficiency of the proposed algorithm, a local winding model of a transformer is built and the fluid field is computed by the conventional LSFEM, dimensionless LSFEM, and the Fluent software. While the fluid and thermal computation results of the local winding model of a transformer obtained by the two LSFEMs are basically consistent with those of the Fluent software, the stiffness matrix, which is formed by the dimensionless scheme of LSFEM and preconditioned by the JPCGM and TSEM, has a smaller condition number and a faster convergence rate of the equations. Thus, it demonstrates a broader applicability.

In order to study the characteristics of the temperature variation in oil-immersed power transformer windings during operation, a two-dimensional transient fluid-thermal coupling calculation method for the transient temperature rising of transformer windings is proposed. Based on the dimensionless least-square finite element method (DLSFEM), the two-dimensional transient fluid-thermal coupling calculation method calculates the velocity distribution of the transformer flow field at different time instants, and based on the upwind finite element method, the temperature distribution at each moment is calculated. Considering the influence of the nonlinear material properties and winding Joule loss on the calculation results, the sequential iteration method is applied to solve the fluid-thermal coupling problem, and finally, the characteristics of the field temperature change are obtained. Compared with the traditional least-square finite element method, the DLSFEM has smaller stiffness matrix number conditions, and the corresponding discrete equations have better convergence. An oil-immersed power transformer winding model is taken as an instance, and the temperature distribution is calculated by the proposed method and the commercial computational fluid dynamic software Fluent. The calculation results of the proposed method are basically consistent with those of Fluent, and its iterative number is much less than that of Fluent, which greatly improves the calculation efficiency.

An improved method to simulate the ion-flow field generated from the corona discharge on HVDC transmission lines is proposed. To remove the oscillations in simulation of charge conservation law, an upwind weighting function is adopted in the finite-element method. The Poisson's equation and the charge conservation law are solved simultaneously through Newton's method of iterations, which accelerates the convergence of the algorithm. A rule for charge density on boundary in the bipolar problem is proposed in this paper, which ensures the stability of the iterations. The computation time, convergence rate, and accuracy of the proposed method are analyzed. The proposed method is verified by analytical and experimental results, and then it is applied to the prediction of the ion-flow field from a ± 1100-kV HVDC transmission line.

In this paper, the capacitance parameter of the overhead transmission lines is calculated by the moment method (MoM), which is based on the image method of electromagnetic theory. The effectiveness of the proposed method is verified by an overhead transmission line model, which has analytical solution. The comparison results show that the relative error between the MoM and analytical solution is small, which shows the accuracy of the program based on the MoM. Then the proposed MoM is applied to calculate the distributed capacitance parameters of three typical overhead transmission lines.

To enhance the computation efficiency and accuracy of three-dimensional steady temperature field of transformer windings, we propose a new non-invasive Reduced Order Model (ROM) based on a mechanism-embedded cascade network. Initially, a snapshot matrix is formed from the Full Order Model (FOM) and then combined with Proper Orthogonal Decomposition (POD) to extract key modal features that characterize the temperature field. Subsequently, a cascade network architecture, integrating Multilayer Perceptron (MLP) and Radial Basis Function Neural Network (RBFNN), is devised to swiftly map working condition parameters to modal coefficients. Additionally, the cascade network is embedded with condition sensitivity and modal contribution mechanisms to further enhance prediction accuracy. Finally, by linearly weighting the modes with predicted modal coefficients, a rapid reconstruction of the steady temperature field in transformer windings is achieved. Validation against Fluent software simulations and experimental measurements demonstrate a close agreement, with computational errors of less than 4K and an impressive single solution time of only 0.0087 s, which is 48760 times faster compared to Fluent software.