以往包含電力系統的各種動態系統模擬,藉由各種控制理論法則如模糊控制理論(Fuzzy Control)及類神經網絡法(Neuronetwork)等,對於輸出及輸入的結果,有秩序地學習系統動態行為特性,而輸出與輸入間未知系統方塊,除可以針對輸入訊號模擬系統輸出響應外,並不具有任何物理意義。 鍵結圖(Bond Graph)法是一套用來分析系統動態行為響應的模擬分析法則,可明確地表示出系統中能量的傳送及轉換現象,也可清楚地描述存在於各領域間能量的轉換行為,所使用元件都符合實際系統物理意義,強調用對的方式來組合原有動態系統的結構,經由因果路徑(CaualPath)建立可分析系統動態行為響應特性,也可依程序轉換成Simulink軟體模組供系統模擬。 本論文將歸納一種程序性的鍵結圖模組轉換方法,用以輔助電力系統建模及分析,針對發電機組加入系統鍵結圖模型建立,以能量觀點探討系統動態行為響應,並建立電力系統單線圖與鍵結圖各元件對應轉換關係,藉由電力系統鍵結圖模型及模擬結果,及依系統鍵結圖模型所建立之因果路徑(CaualPath)關係,評估其對電力系統暫態分析之可行性。
By way of variable control rules such as Fuzzy Control and Neuronetwork, the different dynamic system simulations containing Power System elaborated system movement characters. However, those theories mainly focused on system output simulations. They did not provide any physical meanings about the unknown areas between input and output. Bond Graph is a set of simulative rules to analyze system practical reflection. It could definitely indicate the phenomenon of energy transmissions and conversions. Moreover, the energy transmissions among fields are also clearly described. All used components totally match with physical meanings. It emphasizes on using right ways to organize the original dynamic system structure. The analyzable characters of practical reflections are built through CaualPath. And it also can transform into Simulink software modules for system simulation. To assist power system creation and analysis, this thesis induces a procedural transformation method of Bond Graph module. The method specially focuses on putting Bond Graph models into generation units, investigating system practical reflections from energy point of view, and constructing components transformation relationships between one-line diagrams and Bond Graph. Conclusively, this study provides a feasibility evaluation of power system transient analysis by way of Bond Graph models and simulation results, as well as CaualPath relationship built by Bond Graph modules.