Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/84952
題名: 核能電廠大修排程的最優化
作者: 張維仁
貢獻者: 劉明郎
張維仁
關鍵詞: 排程
大修
混合型整數線性規劃
合併變數
邏輯條件式
啟發性演算法
日期: 2001
上傳時間: 15-Apr-2016
摘要: 隨著經濟的高度成長及電廠興建的日益困難,電力的需求問題是愈來愈嚴重。如何有效率地安排核能機組進行例行性的停機大修及燃料再裝填工作是重要的課題。本論文中考慮核能發電機組五年時程的大修排程問題,我們將這個大修排程問題描繪成一個大型混合型整數線性規劃模型。由於問題的龐大與複雜,此問題的最佳解難以求出。因此,我們發展數個邏輯條件式有效地縮小解集合空間;另外並發展出一個啟發性演算法,採用合併變數法將0/1決策變數合併,使原問題轉成較小的合併模型。先解合併後的合併模型,利用合併模型答案的資訊來固定原始模型的部分變數值之後,再解原始問題。幾個實例計算顯示此演算法的可行性。
Since the growth of economics and the difficulty to build a new power plant, the supply of electric power has become very tight. It is important to ensure the efficient operation of nuclear power plants, including timely shutdown, refueling and maintenance schedule. In this thesis, we deal with the scheduling shutdown and maintenance of nuclear power plants for a five-year time period. This problem can be formulated as a large-scale mixed integer linear problem. The difficulty of solving this problem is due to the large number of binary variables. We then develop several valid logical constraints to reduce the complexity in processing using the branch and bound technique. Also, a heuristic based on the aggregation and dis-aggregation techniques has been developed to yield a good solution. Several examples are given to show the applicability of the algorithm.
封面頁\r\n證明書\r\n論文摘要\r\n目次\r\n表目次\r\n圖目次\r\n第一章 緒論\r\n1.1 前言\r\n1.2 文獻回顧\r\n第二章 核能電廠大修排程的運轉規劃\r\n2.1 電力需求及備載容量\r\n2.2 核能發電系統的運轉規劃\r\n2.3 核能電廠大修排程問題之數學模型\r\n2.4 維修及安全考量的限制式\r\n2.5 邏輯條件式\r\n第三章 變數合併與分解的技術\r\n3.1 合併變數的模型及其上下界\r\n3.2 合併變數的大修排程問題\r\n3.2.1 合併變數的數學模型\r\n3.2.2 運轉決策變數的固定\r\n3.2.3 停機決策變數的固定\r\n3.2.4 啟動決策變數的固定\r\n3.2.5 停機區間已知時的邏輯條件式\r\n3.3 演算法\r\n第四章 實例計算\r\n4.1 實例資料\r\n4.2 實例計算結果\r\n第五章 結論與建議\r\n參考文獻\r\n附錄\r\n附錄一 附表\r\n附錄二 GAMS程式
參考文獻: Bacher, R. (1992) Power system models, objectives and constraints in optimal power flow calculations, in K. Frauendorfer, H. Glsvitsch, and R. Bacher (eds), Optimization in planning and operations of electric power systems, Lecture Notes of a SVOR/ASRO-Tutorial, Thun, Switzerland, October 14-16.\r\nBard, J. F. (1988), Short-term scheduling of thermal-electric generators using Lagrangian relaxation, Operations Research 36(5), 756-766.\r\nBertsekas, D. P., G. S. Lauer, N. R. Sandell, and T. A. Posbergh (1983), Optimal short-term scheduling of large scale power system, IEEE Transactions on Automatic Control 28(1), 1-11.\r\nBienstock, D. and J. F. Shapiro (1988), Optimizing resource acquisition decisions by stochastic programming, Management Science 34(2), 215-229.\r\nBorison, A. B., P. A. Morris, and S.S. Oren (1984), A state-of-the-world decomposition approach to dynamics and uncertainty in electric utility generation expansion planning, Operations Research 32(5), 1052-1068.\r\nBrooke, A., D. Kendrick, and A. Meeraus (1988), GAMS - A user`s guide, The Scientific Press, Redwood City, CA.\r\nEgan, G. T., T. S. Dillon, and K. Morsztyn (1976), An experimental method of determination of optimal maintenance schedules in power system using the branch-and-bound technique, IEEE Transactions on Systems, Man and Cybernetics 6(8), 538-547.\r\nEvans, J. R. (1979), Aggregation in the generalized transportation problem, Computers and Operations Research 6, 199-204.\r\nFourcade, F., E. Johnson, M. Bara, P. Cortey-Dumont (1997), Optimizing nuclear power plant refueling with mixed-integer programming, European Journal of Operational Research 97, 269-280.\r\nFriedlander A., C. Lyra, H. Tavares, and E.L. Medina (1990), Optimization with staircase structure: an application to generation scheduling, Computers and Operations Research 17(2), 143-152.\r\nGAMS Development Corporation, GAMS - The Solver Manual, Washington, DC. Gardner, D. T. (2000), Efficient formulation of electric utility resource planning models, Journal of the Operational Research Society 51, 231-236.\r\nGrowe, N., W. Romisch, and R. Schultz (1995), A simple recourse model for power dispatch under uncertain demand, Annals of Operations Research 59, 135-164.\r\nHuberman, G. (1983), Error bounds for the aggregated convex programming problems, Mathematical programming 26, 100-108.\r\nHallefjord, A., Storoy S. (1990), Aggregation and disaggregation in integer programming problems, Operations Research 38(4), 619-623.\r\nKallio, M. (1977), Computing Bounds for the optimal value in linear programming, Naval Research Logistics 24, 301-308.\r\nMalcolm, S. A. and S. A. Zenios (1994), Robust optimization for power systems capacity expansion under uncertainty, Journal of Operational Research Society 45(9), 1040-1049.\r\nMasse, P. and R. Gibrat (1957), Application of linear programming to investments in the electric power industry, Management Science 3, 149-166.\r\nMendelssohn, R. (1980), Improved bounds for aggregated linear programs, Operations Research 28, 1450-1453.\r\nMerlin, A. and P. Sandrin (1983), A new method for unit commitment at Electricite de Trance, IEEE Transactions on Power Apparatus Systems 102(5), 1218-1225.\r\nModiano, E. M. (1987), Derived demand and capacity planning under uncertainty, Operations Research 35(2), 185-197.\r\nMorton, D. P. (1996), An enhanced decomposition algorithm for multistage stochastic hydroelectric scheduling, Annals of Operations Research 64, 211-235.\r\nMuckstadt, J.A. and S.A. Koenig (1977), An application of Lagrangian relaxation to scheduling in power generation systems, Operations Research 25(3), 387-403.\r\nMuckstadt, J.A. and R. C. Wilson (1968), An application of mixed-integer programming duality to scheduling thermal generating systems, IEEE Transactions on Power Apparatus and System 87(12), 1968-1978.\r\nMurphy, F. H., S. Sen, and A. L. Soyster, (1987) Electric utility expansion planning in the presence of existing capacity: a nondifferentiable, convex programming approach, Computers and Operations Research 14(1), 19-31.\r\nMurphy, F. H. and H. J. Weiss (1990), An approach to modeling electric utility capacity expansion planning, Naval Research Logistics 37, 827-845.\r\nMurphy, F. H. and Z. X. Wang (1993), Network reformulation of an electric utility expansion planning model, Naval Research Logistics 40, 451-457.\r\nNoonan, F. and R. J. Giglio (1977), Planning electric power generation: a nonlinear, mixed integer model employing Benders Decomposition, Management Science 23(9), 946-956.\r\nRamanathan, R., R. Engle, C. W. J. Granger, F. Vahid-Araghi, and C. Brace (1997), Short-run forecasts of electricity loads and peaks, International Journal of Forecasting 13, 161-174.\r\nShaw J. J., R. F. Gendron, and D.P. Bertsekas (1985), Optimal scheduling of large hydrothermal power systems, IEEE Transactions on Power Apparatus Systems 104(2), 286-294.\r\nSoares, S., C. Lyra, and H. Tavares (1980), Optimal generation scheduling of hydrothermal power systems, IEEE Transactions on Power Apparatus Systems 99, 1107-1115.\r\nYellen, J. T., M. Al-Khamis, S. Vemuri, and L. Lemonidis, (1992), A decomposition approach to unit maintenance scheduling, IEEE Transactions on Power Systems 7(2), 726-733.\r\nTurgeon, A. (1978), Optimal scheduling of thermal generating units, IEEE Transactions on Automatic Control 23(6), 1000-1005.\r\nZipkin, P. H. (1980a), Bounds for aggregating nodes in network problems, Mathematical Programming 19, 155-177.\r\nZipkin, P. H. (1980b), Bounds on the effect of aggregating variables in linear programming, Operations Research 28(2), 403-418.\r\n台灣電力公司,台電核能月刊 217期,90年1月。\r\n台灣電力公司, Taiwan Power 1996 Annual Report, Taiwan Power Company, Taipei, Taiwan, ROC.\r\n台灣電力公司全球資訊網網址 http://www.taipower.com.tw/.
描述: 碩士
國立政治大學
應用數學系
資料來源: http://thesis.lib.nccu.edu.tw/record/#A2002001143
資料類型: thesis
Appears in Collections:學位論文

Files in This Item:
File SizeFormat
index.html115 BHTML2View/Open
Show full item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.