Summary
This paper presents an adaptive scheme for predicting out‐of‐step (OOS) condition of synchronous generator based on the Bayesian technique. The proposed scheme performs as an intelligent OOS method for synchronous generators from which by using training variables, the tripping signals are estimated. For classifying target classes between stable and OOS conditions, a series of measurements are derived under various fault scenarios including topological and operational disturbances. The tripping signals are estimated by using feature selection technique based on the Bayesian technique. In this procedure, the data of input variables and corresponding output target classes are implemented as input‐output pair data for Bayesian training and testing. For this propose, the ability of the OOS protective scheme is examined for a number of unseen samples in working mode. The proposed approach is applied on IEEE 39‐bus test system from which by using trained variables, the tripping signals are estimated online. Furthermore, to evaluate the proposed protective scheme in real‐time environment, a 2‐machine experimental case is used to assess the effectiveness of the proposed scheme. The results show a promising performance of proposed protective scheme for proper estimating of tripping signals.
In this paper an optimized Fuzzy based controller is proposed for automatic generation control of two area hydro-thermal power system connected to the wind farm. The parameters and membership functions of the proposed controller are optimized by a modified version of Cuckoo search algorithm (CSA). Also, a weighted objective function is proposed to minimize the frequency deviation and transmission power oscillation. The suggested heuristic objective function is a weight function from maximum frequency drift and oscillations fading time. To assessing the performance of suggested controller, studies is accomplished by two different scenarios. In the first scenario, the simulations are performed without wind farm and in the second scenario, the simulation is done in the presence of a wind farm. The simulation results indicate that the wind farm presence has major effect on sustained improvement of power system and the reason is considering the load variations in the area, the demand electrical energy in the same area is provided by the wind farm and hence, the frequency oscillations are decreased in both areas.
This paper introduces a new single-phase AC-AC converter based on an impedance source circuit. Like the existing single-phase impedance source AC-AC converters, it has the buck-boost ability and direct ac conversion. The input and output voltage possesses the same ground, and the phase angle is maintained and reversed smoothly. The presented converter utilizes a coupled transformer which allows the designer to exploit the transformer’s turns ratio as a variable to attain the desired output voltage. Additionally, the used transformer provides an option to obtain higher voltage gain by decreasing the turns ratio. Hence, smaller size of the coupled inductors is required for the higher voltage cases. To eliminate the switching voltage and current spikes on the power switches, a safe commutation strategy is used instead of utilizing snubber circuits. Furthermore, the input current is continuous and sinusoidal with low harmonics thanks to embedding the input inductor in series with the input source. Additionally, a dynamic voltage restorer is presented based on the proposed converter to compensate the voltage sag and swell faults. Simulation results are provided to evaluate the theoretical analysis. Finally, a laboratory prototype has been fabricated to demonstrate the validation of the presented converter.
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