Geev Mokryani

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Ferroresonance has more damaging effects on transformers and other equipments in distribution networks such as oscillating over voltages and over currents, distortion in voltage and current waveforms, transformer heating, loud noise due to magnetostriction and mal-operation of the protective devices. In this paper the factors that affect the ferroresonance(More)
In this paper an efficient method for detection of inrush current in distribution transformer based on wavelet transform is presented. This method uses Wavelet Transform (WT) and Probabilistic Neural Network (PNN) to discriminate inrush current from other transients such as capacitor switching, load switching and single phase to ground fault. WT is used for(More)
This paper proposes a hybrid optimization method for optimal allocation of wind turbines (WTs) that combines genetic algorithm (GA) and market-based optimal power flow (OPF). The method jointly maximizes net present value (NPV) related to WTs investment made by WTs’ developers and social welfare (SW) considering different combinations of wind generation and(More)
This paper provides a probabilistic method to assess the impact of wind turbines (WTs) integration into distribution networks within a market environment. Combined Monte Carlo simulation (MCS) technique and market-based optimal power flow (OPF) are used to maximize the social welfare by integrating demand side management (DSM) scheme considering different(More)
In this paper, a fuzzy controller for improving the fault ride-through (FRT) capability of variable speed wind turbines (WTs) equipped with a doubly fed induction generator (DFIG) is presented. DFIGs can be used as reactive power sources to control the voltage at the point of common coupling (PCC). The controller is designed to compensate for the voltage at(More)
This paper presents a Wavelet Kernel Fisher Classifier (WKFC) for ferroresonance detection. Using this method Ferroresonance can be discriminate from other transients such as capacitor switching, load switching and transformer switching. Wavelet transform is used for decomposition of signals, feature selection is done by Kernel Principal Component Analysis(More)