Characterization of Power Transformer Frequency Response Signature using Finite Element Analysis

Power transformers are a vital link in electrical transmission and distribution networks. Monitoring and diagnostic techniques are essential to decrease maintenance and improve the reliability of the equipment.This research has developed a novel, versatile, reliable and robust technique for modelling high frequency power transformers. The purpose of this modelling is to enable engineers to conduct sensitivity analyses of FRA in the course of evaluating mechanical defects of power transformer windings. The importance of this new development is that it can be applied successfully to industry transformers of real geometries

A Novel Oil-immersed Medium Frequency Transformer for Offshore HVDC Wind Farms

In this project, a design of an oil type medium frequency transformer for offshore wind farm applications is proposed. The design is intended for applications when series coupling of the output of the DC/DC converters of the wind turbine on their secondary side is done to achieve a cost-effective high voltage solution for collecting energy from offshore wind parks. The focus of the work is on the insulation design of the high voltage side of a medium frequency transformer where the magnetic design constraints should also be satisfied.Above all, a proof of concept is made demonstrating a possible solution for the design of the transformer for such a DC/DC converter unit. The transformer suggested is using oil/paper as insulation medium. Furthermore, characterisation of an eco-friendly biodegradable transformer oil for this type of HVDC transformer application is made. Moreover, an introduction of reliable high frequency characterisation test methods to medium frequency transformer designers is made. In addition, the Non-Linear Maxwell Wagner (NLMW) relations are further developed to form a method for the development of an HVDC MFT transformer. All in all, the DC series concept has been further developed one step closer to pre-commercialization, i.e. from TRL 1 to about 2

Railway interference management: TLM modelling in railway applications

This thesis deals with the application of analytical and numerical tools to Electromagnetic Compatibility (EMC) management in railways. Analytical and numerical tools are applied to study the electromagnetic coupling from an alternating current (AC) electrified railway line, and to study the electrical properties of concrete structure - a widely used component within the railway infrastructure. An electrified railway system is a complex distributed system consisting of several sub-systems, with different voltage and current levels, co-located in a small area. An analytical method, based on transmissions line theory, is developed to investigate railway electromagnetic coupling. The method is used to study an electrified railway line in which the running rails and earth comprise the current retum path. The model is then modified to include the presence of booster transformers. The analytical model can be used to study the railway current distribution, earth potential and electromagnetic coupling - inductive and conductive coupling - to nearby metallic structures. The limiting factor of the analytical model is the increasing difficulty in resolving the analytical equation as the complexity of the railway model increases. A large scale railway numerical model is implemented in Transmission Line Matrix (TLM) and the electromagnetic fields propagated from the railway model is studied. As this work focuses on the direct application of TLM in railway EMC management, a commercially available TIM software package is used. The limitation of the numerical model relates to the increased computation resource and simulation time required as the complexity of the railway model increases. The second part of this thesis deals with the investigation of the electrical properties of concrete and the development of a dispersive material model that can be implemented in numerical simulators such as TIM. Concrete is widely used in the railway as structural components in the construction of signalling equipment room, operation control centres etc. It is equally used as sleepers in the railway to hold the rails in place or as concrete slabs on which the whole rail lines are installed. It is thus important to understand the contribution of concrete structures to the propagation of electromagnetic wave and its impact in railway applications. An analytical model, based on transmission line theory, is developed for the evaluation of shielding effectiveness of a concrete slab; the analytical model is extended to deal with reinforced concrete slab and conductive concrete. The usefulness and limitation of the model is discussed. A numerical model for concrete is developed for the evaluation of the effectiveness of concrete as a shield. Initially, concrete is modelled as a simple dielectric material, using the available dielectric material functionality within TLM. It is noted that the simple dielectric model is not adequate to characterise the behaviour of concrete over the frequency range of interest. Better agreement is obtained with concrete modelled as a dispersive material having material properties similar to that exhibited by materials obeying Debye equation. The limitations of the dispersive material model are equally discussed. The design of conductive concrete is discussed, these have application in the railway industry where old existing structures are to be converted to functional rooms to house sensitive electronic system. A layer of conductive concrete can be applied to the facade to enhance the global shielding of the structure

Numerical and Experimental Evaluation and Heat Transfer Characteristics of a Soft Magnetic Transformer Built from Laminated Steel Plates

The present work evaluates, both experimentally and numerically, the heat transfer characteristics of a 5 kW three-phase transformer built from laminated steel sheets. The transformer is operated at different powers, and its temperature distribution is monitored using 108 thermocouples. The experimental measurements are used firstly to determine the heat dissipated at the core and the windings of the transformer. This information is used as an input for a finite element numerical model, which evaluates the heat transfer characteristics of the transformer. The model proposed in this work simply solves the diffusion equation inside the transformer, accounting for the anisotropic thermal conductivity of the different components of the transformer, together with well-known correlations at its boundaries. The results reveal that the proposed numerical model can correctly reproduce the maximum temperature, the temperature distribution, and the time-evolution of the temperature at specific points of the transformer measured during the experimental campaign. These results are of great use for the subsequent development of transformers of the same type in lab-scale or industrial-scale size and reveal the applicability of simplified numerical models to accurately predict the heat transfer characteristics of this kind of transformers.Eduardo Cano-Pleite acknowledges support from the CONEX-Plus programme funded by Universidad Carlos III de Madrid and the European Union’s Horizon 2020 programme under the Marie Sklodowska-Curie grant agreement No. 801538.Publicad

High frequency finite element modeling and condition assessment of power transformers

Due to the reforming and deregulation of electric power industry, investments in transmission equipment have drastically decreased to meet the economic needs of the competitive market. The electrical utility sector was forced to cut the costs in maintenance and operation without endangering steady supply of electrical power. With this trend, the maintenance strategy desires advanced methods for condition monitoring and assessment of in-service power transformers. Among the common condition assessment techniques, Frequency Response Analysis (FRA) is considered as an efficient off-line diagnostic technique for fault detection in transformer windings. Precise interpretation of the FRA output has proven a great challenge and attracted much effort in recent years. There is also a strong need in this research field to develop an intelligent interpretation procedure for automatic assessment of power transformer conditions. This thesis focuses on two main aspects of power transformer condition assessment: developing an accurate transformer model for the interpretation of transformer FRA responses, and establishing FRA-based novel algorithms to automatically identify transformer failure modes. Reviewing existing transformer modeling methods, this thesis explicitly introduces a simplified distributed parameter model (hybrid winding model) for FRA. The hybrid winding model has the advantage of less computational complexity and high accuracy in simulation results, even in the frequency range above 1 MHz. Analytical expressions for calculating key electrical parameters of winding models are presented. The electrical parameters of transformer windings with a complex or deformed structure are difficult to calculate using analytical formulations. Therefore, computational models based on Finite Element Method (FEM) are developed in this thesis to calculate the frequency-dependent parameters of transformer windings especially with deformed structures. These parameters are then applied to the transformer winding model for frequency response analysis. By applying the electrical parameters obtained from the FEM models, the accuracy of the hybrid winding model has been improved for cases with incipient winding faults. This methodology is implemented in simulation studies of radial winding deformation and minor axial winding movement to reveal the characteristic features of these two types of winding fault. Results show that: (1) frequency-dependent inductances and structure-dependent shunt capacitance derived from FEM models can be used in FRA analysis, (2) by using the proposed methodology, characteristics of frequency response above 1 MHz can be analyzed, (3) regarding radial winding deformation and minor axial winding movement, the changes in the electrical parameters also affect the frequency response in the high frequency range (>1 MHz). A Hierarchical Dimension Reduction (HDR) classifier built on FRA results is proposed in this thesis for condition assessment of power transformers. The algorithms of this classifier make advantageous use of advanced image processing technologies including image binalization and binary erosion in the first step of the procedure. This preprocessing procedure optimizes the measured FRA data by filtering the frequency sections with minor deviations which can effect the calculating results of the indices. Also in this step, FRA diagrams are re-scaled in a linear coordinate system for the convenience of calculating the indices in later step. Subsequently, based on the correlation between electrical properties and features of FRA responses, a division approach is proposed to dynamically divide the frequency range into 5 sub-bands. This division method of frequency range is more reasonable than the conventional methods of fixed frequency sub-bands and more applicable than other existing methods. Then the proposed algorithms of hybrid quantitative indices which include four indices are employed. The dimension reduction for the FRA data is processed by these algorithms in the 5 dynamic frequency sub-bands. It is the first time to establish the algorithms of the hybrid quantitative indices, which include two classical indices and two novel indices, for reducing the dimensions of the FRA data. Two new algorithms of indices, Area Ratio Index (ARI) and Angle Difference (AD), are proposed based on knowledge of FRA interpretation with respect to typical transformer failure modes. They are able to improve the classification performance in terms of the ability to identify electrical failures and the condition of residual magnetization. Based on these advantageous processes, the HDR classifier can aggregate related expertise and approved statistical indices in furtherance of automatic decision analysis on identifying transformer failure modes or conditions. The performance of this classifier has been verified by 32 sets of experimental FRA data, in which 20 sets are primarily used for determination of threshold values of the related algorithms and the rest 12 are purely used for the verification. Results of this implementation of the HDR classifier are 100% accuracy with using the 20 sets of training data and 95.83% accuracy with using the rest 12 sets