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Power transformers are subject to winding and core deformations due to short circuit faults and other environmental conditions. Majority of these faults are of progressive nature and should be rectified as soon as they emerge. Frequency response analysis (FRA) has been widely accepted as a reliable diagnostic tool to detect such faults. As reliable interpretation codes for FRA signatures have not been fully developed and accepted yet, researchers have put much effort to investigate the impact of various mechanical deformations on the transformer FRA signature. Because of the intrusive nature of such faults when staged on a real transformer, most of the studies in the literatures were conducted on a transformer high frequency electric circuit model. Simplifications assumed in these models by ignoring the turn-to-turn capacitance, not taking into account the detailed winding structure and not considering all mutual inductances between coils in various phases have reduced the accuracy of the obtained results. To establish reliable FRA interpretation codes, it is essential to develop electric equivalent circuit models that can yield FRA signature as close as possible to the FRA signature trend of the real transformer. This paper proposes a detailed transformer high frequency electric circuit model which considers the winding structure, inter-turn capacitance and all mutual inductances. Calculation details of the model’s parameters are presented. The accuracy of the proposed model is assessed by comparing its FRA signature with that of an equivalent transformer hardware model during healthy, short circuit disks, radial deformation and axial disks buckling fault.

Power transformers are prone to short circuit faults and external harsh environmental conditions that may result in various internal winding and core deformations. Frequency response analysis (FRA) is the current technique widely used to detect such kind of faults. The technique relies on scanning each phase in a wide frequency range to detect any discrepancies in the winding FRA signature. Current interpretation process for FRA signatures relies on graphical analysis of the magnitude plot without paying much attention to the phase angle plot. This may result in inconsistent analysis for the FRA signature as so far, there is no standardized and automated technique for FRA signature classification. To overcome this limitation, a new polar plot signature based on the integration of the FRA magnitude and phase angle plots has been proposed in the literature. While this new approach has been validated through simulation analysis, its performance on real transformers has not been assessed yet. This paper is aimed at investigating the practical feasibility of replacing the conventional FRA signature with the polar plot and automate the fault diagnosis process using digital image processing techniques. In this context, various winding faults including short-circuit disks, disk space variation, and axial disk buckling have been implemented on a custom-made, Y/Y three phase, 50 Hz, 400 kVA power transformer. The low voltage winding of the investigated transformer comprises 12-turn helical type while the high voltage winding is made of composite structure comprising 10 disks of interleaved winding on the top, 10 disks winding in the middle and 10 disks of continuous winding in the bottom. Impact of various levels and locations of these faults on the FRA polar plot is investigated through extracting digital image texture analysis features. To ease the classification process, a unique classification metric namely image sum square max-min ratio error is calculated based on the extracted features.

As a vital piece of equipment, electronic voltage transformer is widely used in the power system measurements. The current calibration techniques of this asset class exhibit several issues including complex real time implementation. In contrary with existing calibration techniques, this paper proposes a new correction system for electronic voltage transformers, which can be conducted online without causing any interruption to the electricity grid. The new proposed correction system utilizes an SF6 cylinder capacitor and employs an advanced signal processing technique based on the improved Rife frequency shift algorithm. The improved Rife frequency shift algorithm is a combination of the Hanning self-convolution window and the conventional Rife algorithm, which features simple calculation and high accuracy. Results show that the accuracy of the proposed algorithm is higher than the conventional commonly used interpolation algorithms. Compared with the existing traditional calibration techniques, the proposed system features easy online implementation, simple calculation and high accuracy. The robustness of the proposed system is validated through simulation analysis and practical field measurements.

Power management, system stability and communication structure are three key aspects of microgrids (MGs) that have been explored in many research studies. However, the cascaded effect of communication structure on system stability followed by the impact of stability on the power management has not been fully explored in the literature yet and needs more attention. This paper not only explores this cascaded impact, but also provides a comprehensive platform to optimally consider three layers of MG design and operation from this perspective. For generation cost minimization and stability assessment, the proposed platform uses an adaptive particle swarm optimization (PSO) while a new class of data exchange scheme based on IEC 61850 protocol is proposed to reduce the communication time delays among the inverters of distributed generations and the MG control center. This paper also considers the system stability using small-signal model of a MG in a real-time manner as an embedded function in the PSO. In this context investigations have been conducted by modeling an isolated MG with solar farm, fuel cell generator and micro-turbine in MATLAB Simulink. Detailed simulation results indicate the proposed power and stability management method effectively reduces the MG generation cost through maximizing the utilization of the available renewable generations while considering system stability.

In order to promote the practical application of the Rogowski coil-based electronic transformers, it is of great necessity to handle the issues associated with the measurement error and interference in the integral process of the electronic transformer. In this paper, an improved digital integral algorithm with frequency self-adaption ability that aimed at overcoming the above-mentioned issues is proposed. Based on the electronic transformer calibration and harmonic measurement requirements, two specific applications of the proposed integral algorithm are carried out to validate the practical feasibility of the proposed algorithm. Experimental results reveal the improved performance of the Rogowski coil-based electronic transformer equipped with the proposed digital integral algorithm. Errors in harmonic currents measurement (up to 50th order) can be significantly reduced to a level less than 0.01% at a sampling frequency of 12.8 kHz by employing the proposed algorithm. For calibrating electronic transformers, results show that the performance of the proposed algorithm is better than the conventional trapezoidal integral algorithm and Simpson algorithm. Furthermore, the proposed algorithm has the ability to eliminate the impact of frequency fluctuation around the power frequency.

Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results however all current techniques rely on personnel experience more than analytical formulation. As a result, the current techniques do not necessarily lead to the same conclusion for the same oil sample. A significant number of DGA results fall outside the proposed codes of the ratio-based interpretation techniques and cannot be diagnosed using these methods. Moreover, ratio methods fail to diagnose multiple fault conditions due to the mixing up of produced gases. To overcome these limitations, this paper introduces a new fuzzy logic approach that aids in standardizing DGA interpretation and identifies transformer critical ranking based on DGA data. The approach relies on incorporating all traditional DGA interpretation techniques (Roger, Doerenburg, IEC, key gas and Duval triangle methods) into one expert model. In this context, DGA results of 338 oil samples of pre-known fault conditions that were collected from different transformers of different rating and different life span are used to establish the model. Traditional DGA interpretation techniques are used first to analyze the DGA results to evaluate the consistency and accuracy of each method in identifying various faults. Results of this analysis were then used to develop the proposed fuzzy logic model. The model is validated using another set of DGA data that were collected form previously published papers.

A doubly-fed induction generator’s (DFIG’s) sensitivity to external faults has motivated researchers to investigate the impact of various grid disturbances, such as voltage sags and short circuit faults, on its low-voltage ride-through (LVRT) capability. However, no attention has been paid to the impact of internal faults in voltage source converters (VSCs), that interface a DFIG with the grid, on the dynamic performance of the machine. This paper investigates the impacts of various VSC faults, on the dynamic performance and LVRT capability of a DFIG. Faults such as open and short circuit within VSC switches and across the DC-link capacitor are considered in this paper. The impact of internal VSC faults when they occur within the grid side converter (GSC) and rotor side converter (RSC) is investigated. Compliance of the voltage profiles of a DFIG with the LVRTs specified in the recent grid codes of the USA, Spain, Mexico, Denmark, Ireland, Germany, Quebec and the UK are examined for the faults studied. The simulation results show that these faults should be considered in designs of protection systems aimed at avoiding any catastrophic failure of the converter switches or wind turbine.