Sharif Digital Repository

This paper presents a nonlinear geometric approach to fault detection and isolation (FDI) in grid-connected inverters. Faults are considered in inverter switches as well as in grid voltage and source current sensors. The FDI system is not sensitive to load variations or grid transients. No assumptions on balanced, zero-sum or sinusoidal form of voltages or currents are made. The resulting residual converges to zero in no-fault condition such that no threshold adjustment is needed. Simulations demonstrate performance of the proposed FDI system in presence of unknown disturbance. © 2018 IEEE  

CT saturation is a phenomenon that can cause inaccurate fault current measurement and may result in related protective relay failure to block the high current flow under a fault condition in a power system. Hence, it is required to develop a method to detect occurrence of CT saturation with a good accuracy under presence of noise in a power system. In this paper, a new method having the afore-mentioned characteristics is presented. The main benefit of exploiting the introduced approach here for detecting CT saturation is its high level of reliability as well as its reasonable operational speed in CT saturation detection. In other words, these two properties are implemented to this method.... 

In this study, the steady-state operation of the brushless doubly-fed machine (BDFM) in various modes is physically elaborated and the active power flow and torque analysis are presented for each operating mode alongside confirmatory experimental results on a 4/8 pole D160 size machine. The machine behaviour in asynchronous operating modes is described similar to the conventional induction machines with corresponding pole numbers. Moreover, its performance in synchronous mode is shown to be similar to synchronous machines. On the basis of the above, the BDFM performance is further analysed under two possible fault conditions: first, a controller or converter fault leading to loss of... 

As it is found in the related published literatures, the transfer function (TF) evaluation method is the most feasible method for detection of winding mechanical faults in transformers. Therefore, investigation of an accurate method for evaluation of the TFs is very important. This paper presents three new indices to compare the transformer TFs and consequently to detect the winding mechanical faults. These indices are based on estimated rational functions. To develop the method, the necessary measurements are carried out on a 1.3 MVA transformer winding, under intact condition, as well as different fault conditions (axial displacement of winding). The obtained results demonstrate the high... 

This study presents an intelligent fault classification method for identification of transformer winding fault through transfer function (TF) analysis. For this analysis support vector machine (SVM) is used. The required data for training and testing of SVM are obtained by measurement on two groups of transformers (one is a classic 20 kV transformer and the other is a model transformer) under intact condition and under different fault conditions (axial displacement, radial deformation, disc space variation and short circuit of winding). Two different features extracted from the measured TFs are then used as the inputs to SVM classifier for fault classification. The accuracy of proposed... 

In this paper, a new genetic algorithm (GA) method is presented to solve the optimization problem in coordination of overcurrent and earth fault relays. In addition to optimal coordination of overcurrent relays, earth fault relays are also coordinated by GA, considering critical fault condition for the relays located in two sides of network's transformers. The objective function is developed by adding new terms that are the constraints related to the coordination of overcurrent and earth fault relays in critical fault conditions considering different winding arrangements of transformers. The paper concluded by the results of a study carried out on a sample power network. The results...