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標題: 改善彈性交流輸電系統中模糊控制器的設計方法
Improving Design Approach of Fuzzy-Controller in Flexible AC Transmission System
作者: 廖志蒼
Liao, Chih-Chang
關鍵字: 閘控串聯電容器;Thyristor-Controlled Series Capacitor;彈性交流輸電系統;粒子群最佳化;基因演算法;合作型粒子群最佳化;Flexible AC Transmission Systems;Particle swarm optimization;Genetic Algorithm;Cooperative Particle-Swarm Optimization
出版社: 電機工程學系所
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為了提昇在彈性交流輸電系統(FACTS)中模糊控制器的效能,這篇論文提出五種群體智慧最佳化演算法。所設計的模糊控制器結合閘控串聯電容器(TCSC),有效地抑制了低頻振盪及改善了暫態情形。為了確認電力系統穩定度,此論文於輸電線路上使用了三種故障的暫態狀況來模擬抑制後的結果。依據轉速的變量,模糊控制器決定出近似串聯電容器容量,以達到FACTS系統上較佳的動態響應。包括F-CPSO-SK、F-CPSO-HK、F-HGAHPSO、F-HGACPSO-SK 和F-HGACPSO-HK等五種新的群體智慧最佳化演算法,被使用來設計出模糊控制器。F-CPSO-SK和F-CPSO-HK為合作型粒子群最佳化演算法。F-HGAHPSO導入了時變加速係數及慣性加權因數的概念到基因演算法和粒子群最佳化所混合的方法(HGAPSO)中。而F-HGACPSO-SK和F-HGACPSO-HK則導入了合作型架構到HGAPSO之中。與F-HGAPSO的模擬和比較,已經展現出所被提出的這些進化方法的效果和效率。

This thesis proposes five swarm-intelligence optimization algorithms in order to enhance the performance of a fuzzy controller in flexible AC transmission systems (FACTS). The designed fuzzy controller is connected with a thyristor-controlled series capacitor (TCSC) to suppress the low-frequency oscillation effectively and improve the transient situation. To verify the stability of power systems, this thesis uses three fault transient situations in transmission line to simulate the results after suppression. According to the variation of rotation speed, a fuzzy controller determines an approximate series capacitance to achieve a better dynamic response of FACTS. To design the fuzzy controller, five new swarm intelligence optimization algorithms, including F-CPSO-SK, F-CPSO-HK, F-HGAHPSO, F-HGACPSO-SK, and F-HGACPSO-HK, are employed. F-CPSO-SK and F-CPSO-HK are cooperative particle swarm optimization (PSO) algorithms. F-HGAHPSO introduces the concept of the time-varying acceleration coefficients and inertia weight factor into the hybrid of genetic algorithm and PSO (HGAPSO). F-HGACPSO-SK and F-HGACPSO-HK introduce the cooperative framework into HGAPSO. Simulations and comparisons with F-HGAPSO have demonstrated the effectiveness and efficiency of the proposed evolutionary approaches.
其他識別: U0005-0107200920251300
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