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研究生:吳育學
研究生(外文):Yu-Shiue Wu
論文名稱:適應性自動發電控制之模糊邏輯設計
論文名稱(外文):Design of Fuzzy Logic for Adaptive Automatic Generation Control
指導教授:張簡樂仁
指導教授(外文):LeRen Chang Chien
學位類別:碩士
校院名稱:國立成功大學
系所名稱:電機工程學系碩博士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
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 ControlLoad Frequency ControlGain Scheduling
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  • 下載下載:33
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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.
摘 要 III
Abstract IV
誌 謝 V
目 錄 VI
圖 目 錄 X
表 目 錄 XII
符 號 表 XIII
第一章 緒論 1
1.1 研究動機 1
1.2 研究之貢獻 2
1.3 本文架構 2
第二章 系統頻率控制簡介 3
2.1 前言 3
2.2 同步機之基本運轉方程式 3
2.3 負載模型 6
2.4 原動機模型 7
2.5 調速機模型 8
2.6 自動發電控制簡介 11
2.6.1單區域系統之發電控制 11
2.6.2雙區域系統之發電控制 12
2.7 各類型發電機模型 17
第三章 系統參數估測 20
3.1 前言 20
3.2 系統發電響應時間參數(Tw、Tp) 20
3.3 系統慣性常數(M)、頻率響應特性値(β) 24
3.4 電力同步係數(Ptie) 26
3.5 模擬估測試驗 26
第四章 應用基因演算法搜尋表定積分增益 29
4.1 前言 29
4.2 基因演算法(Genetic Algorithm, GA)簡介 29
4.2.1 產生初始族群與定義適應函數 31
4.2.2 編碼(Encoding )及解碼(Decoding) 31
4.2.3 選擇複製(Select & Reproduction) 32
4.2.4 交配(Crossover) 33
4.2.5 突變(Mutation) 34
4.3 以GA搜尋單區域電力系統表定積分增益 35
4.3.1 GA適應函數-- RMS error 35
4.3.2 GA適應函數--F level 37
4.3.3 表定增益控制測試 38
4.3.3.1 步階負載變動測試 38
4.3.3.2 連續負載變動測試 40
4.4 以GA搜尋雙區域電力系統表定積分增益 42
4.4.1 步階負載變動測試 46
4.4.2 連續負載變動測試 48
4.5 討論 50
第五章 以模糊理論建構適應性控制器 51
5.1 前言 51
5.2 模糊集合理論 51
5.2.1 歸屬函數與模糊集合的表示法 52
5.2.2 模糊集合運算子 53
5.2.2.1 補集合(Complement) 53
5.2.2.2 包含(Containment) 54
5.2.2.3 聯集(Union) 54
5.2.2.4 交集(Intersection) 55
5.3 模糊控制器的結構 55
5.3.1 Mamdani模糊控制器 56
5.3.1.1 模糊介面(Fuzzification Interface, FI) 57
5.3.1.2 決策邏輯(Decision-Making Logic, DML) 58
5.3.1.3 解模糊介面(Defuzzification Interface, DFI) 59
5.3.1.4 知識庫(Knowledge Base, KB) 62
5.3.2 Sugeno模糊控制器 62
5.4 Sugeno模糊控制器建構 63
5.4.1 建構單區域電力系統積分增益控制器 63
5.4.2 建構雙區域電力系統積分增益控制器 65
5.5 單區域電力系統Sugeno積分增益控制器測試 66
5.5.1 輸入步階負載測試 66
5.5.2 連續變動負載測試 68
5.5.3 討論 69
5.6 雙區域電力系統Sugeno積分增益控制器測試 70
5.6.1 輸入步階負載測試 70
5.6.2 連續變動負載測試 72
5.6.3 討論 73
5.7 總合比較結論 73
第六章 結論與未來研究方向 74
6.1 結論 74
6.2 未來研究方向 75
附錄一 遞迴最小平方法 76
A1.1 最小平方法(Least Square Algorithm) 76
A1.2 遞迴最小平方法(RLS Algorithm) 76
附錄二 牛頓型演算法應用於線性模型估測 80
A2.1 牛頓型演算法(NTA) 80
參考文獻 82
作 者 簡 介 86
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