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並列摘要


Power System Stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the Low Frequency Oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this Conventional PSS (CPSS) has some problems in power system control and stability enhancement. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this study a new method based on Model Reference Robust Fuzzy Control (MRRFC) is considered to design PSS. In this new approach, in first an optimal PSS is designed in the nominal operating condition and then power system identification is used to obtain model reference of power system including optimal PSS. With changing system operating condition from the nominal condition, the error between obtained model reference and power system response in sent to a fuzzy controller and this fuzzy controller provides the stabilizing signal for damping power system oscillations just like PSS. In order to model reference identification a PID type PSS (PID-PSS) is considered for damping electric power system oscillations. The parameters of this PID-PSS are tuned based on hybrid Genetic Algorithms (GA) optimization method. The proposed MRRFC is evaluated against the CPSS at a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method.

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