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研究生: 柯炫任
Ko, Hsuan-Jen
論文名稱: 以多目標演化演算法求解動態電力調度之成本及汙染問題
A Multiobjective Evolutionary Algorithm for Dynamic Economic Emission Dispatch
指導教授: 蔣宗哲
Chiang, Tsung-Che
口試委員: 鄒慶士
Tsou, Ching-Shih
温育瑋
Wen, Yu-Wei
蔣宗哲
Chiang, Tsung-Che
口試日期: 2022/08/23
學位類別: 碩士
Master
系所名稱: 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2022
畢業學年度: 110
語文別: 中文
論文頁數: 54
中文關鍵詞: 動態電力調度演化演算法多目標限制處理
研究方法: 實驗設計法
DOI URL: http://doi.org/10.6345/NTNU202201580
論文種類: 學術論文
相關次數: 點閱:135下載:15
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  • 在科技發達的社會中,人類對電力的依賴日漸增加。由於目前綠色能源之發展仍在進行,火力發電仍為電力供給的主要方法。動態電力調度之成本及汙染問題為有限制的多目標連續型最佳化問題,給定若干個發電機組資訊和一天二十四小時的電力需求,需求取每小時中各機組的發電量配置。發電配置必須滿足每小時的電力需求,也必須符合各發電機組的負載範圍及調降安全範圍;目標則為同時最小化發電成本和空污排放量。綜合上述,動態電力調度之成本及汙染問題為一具挑戰性之最佳化問題,且有實務應用價值,是非常值得研究的問題。本論文提出多目標差分演化演算法以求解動態電力調度之成本及汙染問題,針對演算法中的合法性修復、環境選擇、計算資源分配及突變選擇四項重要機制進行探究。我們以六組公開測試模型檢驗上述四項機制對求解效能之影響,實驗結果顯示本論文所使用之機制均有良好成效。最後,本論文之方法和十五個既有方法相比,展現優秀的求解能力。

    第一章 緒論 1 1.1 研究背景 1 1.2 問題定義 1 1.2.1 目標函式 1 1.2.2 問題限制 2 1.3 含有限制的多目標最佳化問題 3 1.4 柏拉圖凌越關係 (Pareto dominance) 4 1.5 演化演算法 (Evolutionary Algorithm) 5 1.6 論文架構及貢獻 7 第二章 文獻探討 8 2.1 交配與突變 8 2.2 環境選擇機制 9 2.3 限制處理機制 11 2.3.1 懲罰函式 (penalty function) 12 2.3.2 目標及限制分別比較 (separation of constraints and objectives) 13 2.3.3 限制式目標化 15 2.3.4 混合法 15 2.3.5 修復機制 15 2.4 參數控制 18 第三章 方法與步驟 20 3.1 演算法架構 20 3.2 編碼及族群初始化 22 3.3 個體修復法 22 3.4 鄰居關係與親代選擇 23 3.5 交配與突變 24 3.6 評估方法與環境選擇 25 3.7 動態資源分配 (Dynamic Resource Allocation, DRA) 26 3.8 突變策略的選擇 27 第四章 實驗設計 29 4.1 測試資料及實驗環境 29 4.2 效能指標 29 4.3 演算法參數設定 32 4.4 個體修復法之探討 32 4.5 多目標選擇機制之探討 34 4.6 聚合函式之探討 36 4.7 動態資源分配機制之探討 37 4.8 突變選擇策略之探討 40 4.8.1 動態策略選擇的效果 40 4.8.2 參數的影響 41 4.9 整體效能比較 42 4.9.1 測試資料 5-U 43 4.9.2 測試資料 6-U 44 4.9.3 測試資料 10-U 46 結論與未來方向 50 參考文獻 51

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