淡江大學機構典藏:Item 987654321/38507
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    题名: An optimal design for power system stabilizer by variable structure dynamic grey prediction controller
    作者: 丁鎮權;游建堂;蕭瑛東;黃聰亮
    贡献者: 淡江大學電機工程學系
    关键词: 電力系統穩定器;灰色預測;模糊控制;遺傳演算法;最佳化設計;Power System Stabilizer;Grey Prediction;Fuzzy Control;Genetic Algorithm;Optimal Design
    日期: 2002-12
    上传时间: 2010-01-11 15:24:06 (UTC+8)
    摘要: This paper proposed a new approach to design the power system stablizers (PSS) by utilizing the fuzzy theory, genetic algorithms and grey system theory. The design of a PSS can be formulated as an optimal linear regulator control problem; however, implementing this technique requires the design of estimators. This increases the implementation and reduces the reliability of the control system. Therefore, a favor control scheme that uses only some desired state variables; such as torque angle and speed will be used. To deal with this problem, we use the optimal reduced models to reduce the power system model into two state variables system for each generator and use the variable structure dynamic grey prediction controller to find the control signal of each generator. The grey predictor is adopted to make the next-step prediction for the output states of the power system, the fuzzy system is built to produce an appropriate forecasting step and the GA is used to choose the appropriate parameters of the fuzzy system. Finally, the advantages of the proposed method are illustrated by numerical simulation of the two machines-infinite-bus power systems.
    關聯: 2002中華民國第十屆模糊理論及其應用會議論文集=Proceedings of 2002 Tenth National Conference on Fuzzy Theory and It's Applications，頁41281
    显示于类别:[電機工程學系暨研究所] 會議論文

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