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系統識別號 U0002-2506200911390300
中文論文名稱 非優勢排序遺傳演算法於多水庫系統颱洪操作之規劃
英文論文名稱 Multi-Reservoirs System Flood Operation Planning Using NSGA-II
校院名稱 淡江大學
系所名稱(中) 水資源及環境工程學系碩士班
系所名稱(英) Department of Water Resources and Environmental Engineering
學年度 97
學期 2
出版年 98
研究生中文姓名 郭鑑儀
研究生英文姓名 Chien-I Kuo
學號 696480051
學位類別 碩士
語文別 中文
口試日期 2009-06-04
論文頁數 76頁
口試委員 指導教授-張麗秋
委員-張斐章
委員-施國肱
中文關鍵字 多水庫颱洪操作  NSGA-II  多目標  最佳化 
英文關鍵字 Multi-Reservoirs Flood Operation  NSGA-II  Multi-objective  Optimization 
學科別分類 學科別應用科學環境工程
中文摘要 台灣位於西北太平洋的亞熱帶地區,且颱風頻繁,加上地形坡陡、川短流急,對於颱洪期間如何有效操作水庫之效益,以達到水庫蓄水與防洪減災為重要課題。在多水庫同時進行水庫防洪操作時,需考慮洪水洩放歷程,以避免造成下游匯流口發生嚴重人為失當引發的洪災問題;因此,本研究在探討多水庫聯合防洪操作之規劃,除考慮各水庫的防洪與蓄水之功能外,並考慮下游匯流口之洪水歷程。
本研究以多水庫操作最佳化為目標,運用多水庫防洪操作運轉辦法及相關水庫硬體限制建立防洪運轉模式,以搜尋多水庫防洪最佳洩放歷程,利用非優勢排序遺傳演算法(Non-dominate Sorting Genetic Algorithm , NSGA-II)搜尋水庫最佳洩放歷程,探討水庫操作之合理性。本研究以石門與翡翠兩水庫系統以及該匯流處為研究對象,以非優勢排序遺傳演算法搜尋之結果顯示將有效達到洪峰消減並儲存洪水以滿足期末水位以利未來供水運用。
英文摘要 Taiwan is located in the Northwestern Pacific Ocean subtropical jet stream monsoon district and frequently hit by Typhoon. Because the steep mountainous landform makes most of the rainfall flow immediately into the ocean with a few hours, the river cannot keep enough water for future use. Reservoirs have become the most import and effective floodwater storage facilities. The huge flood often exceeds the capacity of the reservoirs; consequently, attention must focus on improving the operational effectiveness and efficiency of existing reservoirs for maximizing the beneficial use of water storage and decreasing the flood peak stage downstream. Especially, for the flood operation of the multi-reservoir system, it should prevent the downstream from a serious man-made flood.
This study proposes a multi-reservoir flood operation optimization model with linguistic flood control requirement and existing operational regulations for providing the information of rational multi-reservoir flood operating decisions. The approach involves formulating multi-reservoir flood operation as an optimization problem and using the non-dominate sorting genetic algorithm (NSGA-II) as searching engines. The proposed approach was applied to the problem of finding the optimal release and desired storage, taking the multi-reservoir system of Shihmen and Feitsui reservoirs as a case study. The decrease rates of flood peak of two reservoirs and the junction are considered as the multi-objective functions. The results demonstrated that NSGA-II could effectively provide rational flood operating decisions of the multi-reservoir system to reduce flood damage during typhoon periods and to increase final storage for future usages.
論文目次 謝誌 I
中文摘要 II
ABSTRACT III
章節目錄 V
表目錄 VIII
圖目錄 IX
一、前言 1
1.1研究動機 1
1.2研究目的與方法 2
二、文獻回顧 3
2.1遺傳演算法的應用 3
2.2水資源方面的應用 3
三、理論概述 6
3.1遺傳演算法 6
3.1.1遺傳演算法之基本架構 7
3.2非優勢排序遺傳演算法 7
3.2.1非優勢排序遺傳演算法之基本元素與運算子 10
3.2.2多目標遺傳演算法之特性 14
四、研究案例 16
4.1水庫簡介 16
4.1.1石門水庫簡介 16
4.1.2翡翠水庫簡介 17
4.1.3匯流口簡介 17
4.2水庫防洪操作 18
4.2.1石門防洪運轉操作規則 18
4.2.2翡翠防洪運轉操作規則 19
4.2.3相關水利法規 20
4.3颱風資料蒐集與分析 20
4.4多水庫聯合防洪操作之決策模式 22
4.5非優勢排序遺傳演算法(NSGA-II) 28
4.5.1運算方法及相關參數設定 28
4.5.2搜尋範圍設定 29
4.5.3結果 31
4.5.4改變初始水位搜尋之結果 48
五、結論與建議 50
5.1結論 50
5.2建議 51
參考文獻 53
附錄A 石門水庫以NSGA-II搜尋之洩放趨勢圖 57
附錄B 翡翠水庫以NSGA-II搜尋之洩放趨勢圖 67
表目錄
表4.1石門與翡翠水庫颱風資料 21
表4.1石門與翡翠水庫颱風資料(續) 22
表4.2相關設定參數 28
表4.3歷時40小時的颱風限制式個數 28
表4.4 石門與翡翠水庫於NSGA-II與原操作之防洪操作結果比較 32
表4.4石門與翡翠水庫於NSGA-II與原操作之防洪操作結果比較(續) 33
表4.5 匯流口NSGA-II與原操作之洪峰消減率比較 33
表4.5 匯流口NSGA-II與原操作之洪峰消減率比較(續) 34

圖目錄
圖3.1 Pareto鋒線示意圖 8
圖3.2 非優勢排序遺傳演算法流程圖 9
圖3.3 實數編碼組成之範例 10
圖4.1兩水庫系統與下游匯流口位置圖 18
圖4.2石門水庫運轉規線示意圖 24
圖4.3翡翠水庫運轉規線示意圖 24
圖4.4洪峰發生前後階段區別示意圖 27
圖4.5碧利斯颱風(石門)搜尋之洩放量與水庫水位趨勢圖 36
圖4.6碧利斯颱風(翡翠)搜尋之洩放量與水庫水位趨勢圖 37
圖4.7 歐馬颱風(石門)搜尋之洩放量與水庫水位趨勢圖 38
圖4.8歐馬颱風(翡翠)搜尋之洩放量與水庫水位趨勢圖 39
圖4.9賀伯颱風(石門)搜尋之洩放量與水庫水位趨勢圖 40
圖4.10賀伯颱風(翡翠)搜尋之洩放量與水庫水位趨勢圖 41
圖4.11艾利颱風(石門)搜尋之洩放量與水庫水位趨勢圖 42
圖4.12艾利颱風(翡翠)搜尋之洩放量與水庫水位趨勢圖 43
圖4.13納莉颱風(石門)搜尋之洩放量與水庫水位趨勢圖 44
圖4.14納莉颱風(翡翠)搜尋之洩放量與水庫水位趨勢圖 45
圖4.15利奇馬颱風(石門)搜尋之洩放量與水庫水位趨勢圖 46
圖4.16利奇馬颱風(翡翠)搜尋之洩放量與水庫水位趨勢圖 47
圖4.17(改)賀伯颱風(石門)搜尋之洩放量與水庫水位趨勢圖 48
圖4.18(改)賀伯颱風(翡翠)搜尋之洩放量與水庫水位趨勢圖 49
參考文獻 (1)Chang, J.X., Huang, Q. and Wang, Y.M. 2005. Genetic algorithms for optimal reservoir dispatching. Water Resour. Manage. 19:321-331.
(2)Chang, L.C. and Chang, F.J. 2001. Intelligent control for modeling of real time reservoir operation. Hydrological Processes 15:1621-1634.
(3)Chen, L., McPhee, J. and Yeh, W. W.-G. 2007. A diversified multiobjective GA for optimizing reservoir rule curves. Advances in Water Resources 30 (2007) 1082-1093.
(4)Deb, K. and Goyal, M. 1996. A combined genetic adaptive search (GeneAS) for engineering design. Computer Science and Informatics 26(4), 30-45.
(5)Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. 2002.A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2, pp. 182-197.
(6)Deb, K. 2001. Multi-objective Optimization Using Evolutionary Algorithms, John Wiley & Sons, Chichester, pp. 389-400.
(7)Deb, K. 1995. Optimization for Engineering Design: Algorithms and Examples. New Delhi: Prentice-Hall
(8)Elferchichi, A., Gharsallah, O., Nouiri, I., Lebdi, F. and Lamaddalena, N. 2009. The genetic algorithm approach for identifying the optimal operation of amulti-reservoirs on-demand irrigation system. Biosystems engineering I02: 334-344.
(9)Fahmy, H.S., King J.P., Wentzel M.W. and Seton J.A. 1994. Economic optimization of river management using genetic algorithms. ASAE 1994
(10)Fonseca, C.M. and Fleming, P.J. 1993. Genetic Algorithms for Multiobjective Optimization:Formulation, Discussion and Generalization. Dept. Automatic Control and Systems Eng. University of Sheffield Sheffield S1 4DU, U.K.
(11)Goldberg, D.E. 1989. Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addisson-Wesley
(12)Holland, J.H. 1975. Adaptation in Natural and Artificial Systems, Ann Arbor, MI: The University of Michigan Press.
(13)Hsu, N.S. and Wei, C.C. 2007. A multipurpose reservoir real-time operation model for flood control during typhoon invasion. Journal of Hydrology 336:282-293.
(14)International Summer Meeting. American Society of Agricultural Engineers., St. Joseph, Michigan, USA
(15)Mehrd, H.A., Ghodsypour, S.H. and Kerachian, R. 2009. Multi-objective genetic local search algorithm using Kohonen’s neural map. Computers & Industrial Engineering
(16)Ngo, L.L., Madsen, H. and Rosbjerg, D. 2007. Simulation and optimization modeling approach for operation of the Hoa Binh reservoir ,Vietnam. Journal of Hydrology 336:269-281.
(17)Oliveira, R. and Loucks, D.P. 1997 Operating rules for multireservoir system. Water Resour. Res. 33(4): 839-852.
(18)Reedy, M.J. and Kumar, D.N. 2006. Optimal Reservoir Operation Using Multi-Objective Evolutionary Algorithm. Water Resources Management 20: 861–878.
(19)Wardlaw, R. and Sharif, M. 1999. Evaluation of genetic algorithms for optimal reservoir system operation. J. Water Resour. Plan. Manage. Div. ASCE 125(1): 25-33.
(20)Zahraie, B. and Mossa Hosseini, S. 2009. Development of reservoir operation policies considering variable agricultural water demands. Expert Systems with Applications 36: 4980-4987.
(21)陳莉,1995,以物件導向之傳演算法優選水庫運用規線之研究,國立台灣大學農業工程學系博士論文
(22)蕭金財、張良正,1998,多目標水庫序率最佳操作模式之建立與應用,台灣水利 46(1): 72-83
(23)向子菁,1999,智慧型控制理論於水庫操作決策之研究,國立台灣大學農業工程研究所碩士論文
(24)蕭金財、張良正,2000,應用平行序率最佳控制演算法於多目標水庫系統之優選操作,中國土木水利工程學刊 12(3): 551-560
(25)邱昱禎,2003,模糊規劃理論與優選法於水庫操作之研究,國立臺灣大學生物環境系統工程學系暨研究所
(26)王國威,2006,運用懲罰機制遺傳演算法於水庫颱洪操作之規劃,淡江大學水資源及環境工程學系暨研究所
(27)經濟部水利署北區水資源局,石門水庫水門操作規定,2005
(28)經濟部水利署北區水資源局,石門水庫營運四十年特刊,2005
(29)經濟部水利署北區水資源局,經濟部石門水庫運用要點,2005
(30)經濟部水利署北區水資源局,經濟部翡翠水庫運用要點,2004
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