Steven D. Mitchell

Modeling Power Transformers to Support the Interpretation of Frequency-Response Analysis

A power transformer will yield a frequency response which is unique to its mechanical geometry and electrical properties. Changes in the frequency response of a transformer can be potential indicators of winding deformation as well as other structural and electrical problems. A diagnostic tool which leverages this knowledge in order to detect such changes is frequency-response analysis (FRA). To date, FRA has been used to identify changes in a transformers frequency response but with limited insight into the underlying cause of the change. However, there is now a growing research interest in specifically identifying the structural change in a transformer directly from its FRA signature. The aim of this paper is to support FRA interpretation through the development of wideband three-phase transformer models which are based on three types of FRA tests. The resulting models can be used as a flexible test bed for parameter sensitivity analysis, leading to greater insight into the effects that geometric change can have on transformer FRA. This paper will demonstrate the applicability of this modeling approach by simultaneously fitting each model to the corresponding FRA data sets without a priori knowledge of the transformers internal dimensions, and then quantitatively assessing the accuracy of key model parameters.

The Influence of Complex Permeability on the Broadband Frequency Response of a Power Transformer

This paper considers the effect of the complex permeability of a power transformer core on the frequency response analysis (FRA) test spectrum. Current work in FRA generally neglects the core beyond a few hundred kHz. This research demonstrates that the effective complex permeability is significant at 1 MHz and greater than unity at frequencies exceeding 15 MHz. The paper also shows that for broadband small signal testing, such as FRA, the low field conditions induced by the injected signal result in a relative permeability that approaches the initial permeability of the core. This ensures that the relative permeability remains approximately constant over a large range of frequencies and will have a degree of independence with respect to the amplitude of the injection voltage.

Initial Parameter Estimates and Constraints to Support Gray Box Modeling of Power Transformers

An accurate transformer model is an important tool for use in the study of power transformers. However, a manufacturers proprietary restrictions will generally make access to the detailed design specifications of a transformer difficult. Therefore, in order to construct a physically representative transformer model, it is often necessary to estimate the model parameters. One approach is to fit the model to data obtained from tests, such as frequency-response analysis. However, during the process of fitting a model to a data set, it is critical that the estimated parameters appropriately represent the transformer under test. An estimator that is not constrained can converge on a parameter set which may satisfy the objective function but is not physically representative of the transformer. It is therefore important to constrain the model parameters. The aim of this paper is to formulate a methodology to obtain initial estimates and constraints for several fundamental transformer parameters. To demonstrate applicability, the initial parameter estimates and constraints are applied to a range of distribution transformers of varying age and manufacture, ranging in size from 200 kVA to 18 MVA.

Wideband parametric identification of a power transformer

This paper applies a recently developed technique for wideband frequency domain system identification to parametric modelling of a power transformer using frequency response data. It is well known that frequency response data from a typical power transformer contains many resonant modes and spans several decades in frequency. This in effect leads to a numerically ill-conditioned problem when attempting to fit a parametric model to the data. The method employed here to fit the parametric model utilises what has been termed frequency localising basis functions. These functions have been shown to improve the numerical conditioning of a least squares type estimator which correspondingly results in an increased accuracy of the estimated parameters. Two examples are used in this paper to highlight the veracity of the frequency localising basis functions technique. The first example uses simulation data, whilst the second utilises frequency response data from a large power transformer.

DC power vs AC power for mobile mining equipment

This paper proposes the use of DC distribution systems in mining applications. In mining a considerable attention is paid to cost optimization per ton of material moved. Therefore, there is a continuous push to use more efficient machines and systems. Electric dragline is the largest excavating machine used in mining, with the least cost per ton and the highest productivity. Any improvement of their electrical system would result in a significant energy saving. On the other hand, DC distribution is an effective method of power delivery which offers a number of advantages including lower electric losses, integration of small distributed generation, better power quality and stability. In this paper, draglines are considered as a case study to verify feasibility of DC distribution systems, in both delivery to a dragline across the mine site and power distribution inside the dragline. Several scenarios are considered, showing the advantages of DC power distribution for DC-based draglines, AC-based draglines, and for effective transition from DC- to AC-based. It will be shown that 12-15% efficiency improvement can be achieved by using the DC distribution system. Moreover, there exist a clear potential for integration of renewable energy sources and energy storage devices, to further improve stability and energy efficiency.

Powering Mobile Mining Machines: DC Versus AC Power

To achieve higher profitability, an important objective in mining applications is to minimize the cost per ton of material moved, which leads to the use of more efficient mining machines and systems. Among open-cut excavating machines, preference is often given to electric draglines and rope shovels due to their high productivity and efficiency. Since they are the biggest machines in a mine, any efficiency improvements to their electric systems would result in significant energy savings. The dc distribution has been historically known as an effective method of power delivery. Due to recent developments in power electronics, dc distribution systems are now being seriously considered for various medium-voltage (MV) applications.

Advanced fault tolerance strategy for DC microgrids in mining excavators

Recently, DC microgrids have become a viable option for mining distribution systems. Fault diagnostics and protection are known challenges in DC microgrids. In this paper, we present an overview of the existing strategies for fault diagnostics and protection of a DC microgrid and apply them to an open cut DC mine scenario, which includes large electric excavators. We propose a comprehensive fault tolerance strategy based on analysis of electrical and mechanical operations of an electric rope shovel and identification of its working cycle. Based on this strategy, in case of a fault, the electric rope shovel will be able to perform required actions to avoid collisions and safely finish its working cycle, while maintaining electric safety.

Permeability and its Influence on the Broadband Frequency Response of a Power Transformer

This paper considers the effect of the complex permeability of a power transformer core for the full FRA test spectrum (typically less than 10 MHz). Current work in the area generally neglects the core beyond a few 100 kHz. This paper demonstrates that the relative complex permeability is significant at 1 MHz and above unity until frequencies beyond 15 MHz. The paper also demonstrates that for broadband small signal testing, such as FRA, the low field conditions induced by the injected signal result in a relative permeability that approaches the initial permeability of the core. This ensures that the relative permeability remains approximately constant over a large range of frequencies and will have a degree of independence with regards to the injection voltage source.

Practical implementation of a narrowband high frequency distributed model for locating partial discharge in a power transformer

This paper proposes the use of a narrowband high frequency based distributed transformer model for estimating partial discharge location within the winding of an interleaved power transformer. At high frequencies, the residual inductance within a transformer winding becomes significant This inductive interaction generates its own characteristic response which, due to its distributed nature, can be utilized for partial discharge location. The technique proposed here takes advantage of the high frequency nature of a partial discharge and requires measurement at one location only. It also does not require detailed knowledge of the transformers physical and material specifications. To confirm this approach, practical tests were conducted on a 66 kV/25 MVA interleaved transformer winding. The partial discharge injection was delivered by an oil immersed point-plane 7.5 kV source with the data captured using a current probe on the earth terminated neutral.

Estimation of physical transformer parameters from frequency response analysis

The wideband frequency response of a power transformer will yield a signature unique to its mechanical geometry. A change in the frequency response can be indicative of winding deformation. Frequency Response Analysis (FRA) is a diagnostic tool used to monitor frequency response changes. The aim of this paper is to facilitate FRA interpretation through the development of a three phase transformer model that is based on the estimation of physical parameters. The paper will demonstrate the applicability of the model by using FRA data sets of a 1.3MVA distribution transformer and assessing the accuracy of key parameter estimates.