| 研究生: |
吳育學 Wu, Yu-Shiue |
|---|---|
| 論文名稱: |
適應性自動發電控制之模糊邏輯設計 Design of Fuzzy Logic for Adaptive Automatic Generation Control |
| 指導教授: |
張簡樂仁
Chien, LeRen Chang |
| 學位類別: |
碩士 Master |
| 系所名稱: |
電機資訊學院 - 電機工程學系 Department of Electrical Engineering |
| 論文出版年: | 2008 |
| 畢業學年度: | 96 |
| 語文別: | 中文 |
| 論文頁數: | 87 |
| 中文關鍵詞: | 自動發電控制 、增益調節 、負載頻率控制 |
| 外文關鍵詞: | Automatic Generation Control, Load Frequency Control, Gain Scheduling |
| 相關次數: | 點閱:67 下載:3 |
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一般自動發電控制中,積分回授控制是相當重要且常見的控制模式,所以在這種狀況下,積分回授增益(Ki)的選擇就顯得相當重要。因此本文提出依電力系統特性改變Ki值的適應性模糊控制器:以遞迴式最小平方(RLS)演算法估測系統特性參數,模糊控制器則以這些參數為輸入來決定Ki 的設定。在本文中將介紹RLS 系統參數估測器的建構,以及如何以基因演算法(GA)在不同系統特性下找出適合的積分增益,並依此來設計模糊控制器。最後藉由模擬測試驗證本文提出的模糊控制器確實能提高自動發電控制的性能。
Integral control is a very common but essential technique that is used in Automatic Generation Control (AGC). Therefore, the setting of integral gain(Ki) is relatively important. This thesis proposes a fuzzy type self-tuning controller to set Ki according to power system’s operating states. At first, RLS algorithm is used to estimate system’s dynamic parameters, then a fuzzy logic will be utilized to set Ki according to those estimated parameters. This thesis introduces the structure of the RLS parameter estimaters, the GA algorithm for searching proper Ki value according to available nominated states, and fuzzy logic for considering adnominal states. Simulation results show that the adaptive fuzzy controller effectively enhance the performance of the AGC.
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