In this paper, a novel method based on image processing is proposed for detecting the presence and location of mechanical deformations on an actual power transformer winding. A vertical imaging setup is used to obtain a twodimensional (2-D) image of the transformer winding using synthetic aperture radar (SAR) imaging method and Kirchhoff migration algorithm. The main goal of the image processing method is to detect the location of the radial deformation on the transformer high-voltage (HV) winding. Two different deformations are applied on the winding under the test in this paper. The first one is a modeled bulgy mechanical deformation and the second one is an actual concave buckling made on the actual transformer HV winding. The experimental results for different cases show the effectiveness of the proposed method to detect the presence and location of the deformation on the transformer winding.

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Summary Flexible AC transmission system (FACTS) devices such as static synchronous series compensators, static synchronous compensators, and unified power flow controllers which use voltage source convertors (VSCs) can noticeably improve different characteristics of power systems. Therefore, finding their optimal allocation is a vital issue. To find the optimized placement of different FACTS devices, it is necessary to calculate the effects of such devices in the whole system. Sensitivity analysis has been recently proposed as a fast and reliable method to find the effects of voltage source convertors on system variables. In this paper, a novel approach is introduced to optimize the allocation of different FACTS devices based on the equivalent impedance model obtained from sensitivity analysis. This method requires neither the exact modeling of voltage source convertors nor more than one load flow, so it is much faster than conventional methods. Due to its simplicity and fastness, it can cover all possible locations, continuous sizing, type, and number of compensators. Therefore, its performance and accuracy are considerably high. The proposed method based on a novel objective function, which includes voltage profile, transmission capability, and stability, is applied to a typical 6‐bus and the 30‐bus IEEE test systems. Furthermore, genetic algorithm is implemented to solve the optimization problem. The test results illustrate the effectiveness of the introduced method. Copyright © 2014 John Wiley & Sons, Ltd.

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Medium-voltage distributed generation (DG) units can be subjected to a high penetration level of dynamic loads, such as induction motor (IM) loads. The highly nonlinear IM dynamics that couple active power, reactive power, voltage, and supply frequency dynamics can affect the stability of MV grid-connected converter (GCC)-based DG units. However, detailed dynamic analysis and, more importantly, stabilization approaches of GCC-based DG units with IM loads when subjected to the grid faults, are not reported in the current literature. In addition, the literature lacks a thorough study on the effect of the grid strength on the low-voltage ride-through (LVRT) performance of such practical systems. To fill in this gap, this paper presents comprehensive integrated modeling, stability analysis, and LVRT performance improvement methods for GCC-based DG units in the presence of an IM load considering different grid strengths. A detailed multi-stage small-signal model of the complete system is obtained, and the eigenvalue analysis is conducted considering both static and dynamic load modeling. Furthermore, a sensitivity analysis is performed to investigate the effect of the length of the power line between the DG unit and the IM on the stability and LVRT performance of the entire system. Finally, the LVRT performance of the DG unit under an unbalanced grid fault is investigated using three different reference current generation strategies to determine the best strategy to provide a stable and efficient LVRT performance under strong and weak grid conditions. The time-domain simulation and experimental results are also presented to validate the effectiveness of the proposed methods.