台灣的用電來源主要來自於火力發電。火力機組雖然有發電成本低廉、供電穩定等優點，但發電過程產生的二氧化碳排放會加劇整個地球之溫室效應，以及化石燃料資源逐年減少等問題皆為實際規劃電力調度時必須面臨之議題。至此，如何規劃出一套能同時兼顧經濟效益、環保效益和輸電效率之多目標動態電力調度模型，為本論文致力之研究重點。

本文的調度目標包括發電成本、二氧化碳排放量以及線路損失，由於這3個目標項目在性質方面皆有所不同，在此必須透過多目標規劃技巧同時對所有的目標反覆進行讓步、協調來得出符合整體效益之調度解。首先以本文提出的改良型進化規劃法(IMEP)結合最佳化電力潮流(OPF)求取各個目標對應之最佳解與劣等解，然後對於多目標規劃，考量到現實情況中決策者對於調度目標所掌握的相關資訊可能為充足的或者不足的，於此分別提出目標規劃法與模糊多目標規劃法並搭配上述的演算法與電力潮流做多目標規劃求解。最後本文以IEEE 30 Bus為測試系統，模擬分別在單一目標、雙目標與多重目標情境時所規劃出的調度解，並比較其中之差異。經測試後證明了本文提出的兩種多目標規劃方法均能同時兼顧發電成本、二氧化碳排放量以及線路損失等調度目標之求解品質。

The main electricity sources in Taiwan are from thermal power plants. Although thermal unit has the advantages of low cost and stable delivery, the problem of global warming caused by emission and the reduction of fossil fuels need to be considered for the power dispatch. How to design the dynamic power dispatch model that can consider the economic, environmental protection and transmission efficiency simultaneously is the main subject in this thesis.

The objectives in the dynamic power dispatch problem are power generation cost, emission and line loss. Because the property of all three objectives are different, do the coordination of all objectives are important and the technic of multiple objectives programming is used in this research. To the beginning, Improved Evolutionary Programming(IMEP) algorithm and Optimal Power Flow(OPF) were used to get the best solution and the worst solution for each of the objectives. For multiple objectives, Goal Programming method and Fuzzy Multiple Objectives Programming method were combined to deal with the multi-objectives where the decision maker could have sufficient data or insufficient data related to each objective. The single objective, double objectives and triple objectives power dispatch simulations were conducted for the IEEE 30 Bus system.

論文審定書…………………………………………………………………………….i
誌謝……………………………………………………………………………………ii
摘要……………………………………………………………………………...……iii
Abstract ...…………..……………………………………………………….………...iv
目錄…………………………………………………………………………………....v
圖次………………………………………………………………………………….viii
表次…………………………………………………………………………………...xi

第一章 緒論…………………………………………………………………………..1
1.1 研究背景與動機……………………………………………………………...1
1.2 研究方法與目的……………………………………………………………...2
1.3 論文架構……………………………………………………………………...4

第二章 電力調度相關問題描述與數學模型推導…………………………………..5
2.1 動態經濟調度問題描述……………………………………………………...6
2.2 最佳化電力潮流……………………………………………………………...7
2.2.1 具常數亞可比矩陣之負載潮流模型推導………………………………8
2.2.2 電壓控制匯流排模型推導……………………………………………..11
2.3 電力調度相關數學模型描述……………………………………………….15
2.3.1 目標函數………………………………………………………………..15
2.3.2 等式限制式……………………………………………………………..17
2.3.3 不等式限制式…………………………………………………………..19

第三章 演算法設計和測試…………………………………………………………22
3.1 進化規劃法(EP)……………………………………………………………..23
3.2 改良型進化規劃法(IMEP)………………………………………………….27
3.2.1 前言……………………………………………………………………..27
3.2.2 改良型進化規劃法的設計……………………………………………..28
3.2.3 選擇模式的修改和比較………………………………………………..33
3.3 演算法強韌性測試………………………………………………………….36
3.3.1 最低發電成本測試……………………………………………………..37
3.3.2 最低二氧化碳排放量測試……………………………………………..39
3.4 應用IMEP與OPF於動態電力調度研究流程規劃………………………41

第四章 多目標規劃分析……………………………………………………………45
4.1 多目標規劃的定義與特性………………………………………………….46
4.2 常見的多目標規劃方法…………………………………………………….48
4.2.1 權重法…………………………………………………………………..48
4.2.2 限制法……………………………………………………………….49
4.2.3 效用函數法……………………………………………………………..49
4.3 研究方法…………………………………………………………………….50
4.3.1 目標規劃法……………………………………………………………..50
4.3.2 模糊多目標規劃法……………………………………………………..53
4.3.3 兩方法特性比較………………………………………………………..58
4.4 多目標動態電力調度規劃流程說明……………………………………….59

第五章 系統測試與案例分析………………………………………………………64
5.1 單一目標最佳化調度測試………………………………………………….71
5.1.1 最低發電成本調度策略………………………………………………..71
5.1.2 最低二氧化碳排放量調度策略………………………………………..73
5.1.3 最低線路損失調度策略………………………………………………..74
5.1.4 案例比較………………………………………………………………..76
5.2 雙目標規劃調度測試……………………………………………………….79
5.2.1 有明確目標資訊之調度規劃…………………………………………..79
5.2.2 無明確目標資訊之調度規劃…………………………………………..83
5.3 多重目標規劃調度測試…………………………………………………….87
5.3.1 有明確目標資訊之調度規劃…………………………………………..87
5.3.2 無明確目標資訊之調度規劃…………………………………………..92
5.4 案例整理與探討…………………………………………………………….97

第六章 結論與未來研究方向……………………………………………………..101
6.1 結論………………………………………………………………………...101
6.2 未來研究方向……………………………………………………………...102

參考文獻……………………………………………………………………………104
附錄…………………………………………………………………………………109

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