簡易檢索 / 詳目顯示

研究生: 黃艾力
Riyanto, Eri
論文名稱: 改進既有用水網路操作彈性之經驗翻修策略
A Heuristical Revamp Strategy to Improve Operational Flexibility of Existing Water Networks
指導教授: 張珏庭
Chang, Chuei-Tin
學位類別: 碩士
Master
系所名稱: 工學院 - 化學工程學系
Department of Chemical Engineering
論文出版年: 2009
畢業學年度: 97
語文別: 英文
論文頁數: 106
中文關鍵詞: 經驗翻修MINLP水網路彈性指標
外文關鍵詞: water network, revamp heuristics, flexibility index, MINLP
相關次數: 點閱:129下載:1
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 在本研究中,我們發展出增進化工廠中既有水網路操作彈性的經驗性翻修策略,具體言之,即利用文獻中已發展成熟的彈性指標 (Swaney and Grossmann, 1985) 來定量描述任何給定水網路適應不確定干擾之能力。由於彈性指標模型是一個混合整數非線性規劃 (MINLP) 模式,我們無法保證相應最佳化過程的收斂,因此提出了兩個能求解促進效率的技巧:(一) 將給定網路消耗最小純水量時的操作條件,當作該規劃的初值,(二) 利用Bandoni (2000) 提出的平滑函數來消除MINLP模型的二元變數。另外,我們也根據解決大量的簡易例題獲得的經驗,發展出一系列能放寬彈性指標模型最佳解中觸發條件的翻修設計方案,除了增加純水供應率的上限以外,我們還考慮兩個修改結構的方法為:(一) 加入或刪除連接管線,(二) 增加新的廢水處理單元或取代既有廢水處理單元。最後,我們以一系列的案例研究來展示上述策略的可行性及有效性。

    A heuristical revamp strategy is developed in this work to improve the operational flexibility of existing water networks. The well-established concept of flexibility index (Swaney and Grossmann, 1985) is adopted for quantitatively characterizing the ability of any given water network to cope with all uncertain disturbances. Since the flexibility index model is a mixed-integer nonlinear program (MINLP), the convergence of the corresponding numerical optimization process is not guaranteed. Two solution techniques have been developed to promote efficiency, namely, (1) generating the initial guesses by minimizing freshwater consumption rate of the nominal network, and (2) incorporating the smoothing functions suggested by Bandoni et al. (2000) to eliminate the binary variables in the MINLP model. A set of design heuristics have also been developed to identify possible revamp measures to relax the active constraints in the optimal solution of flexibility index model. This flexibility enhancement approach was derived empirically from the insights gained in solving a large number of simple examples. Other than increasing the upper limit of freshwater supply rate, two structural modifications are considered as the main revamp options, i.e., (1) inserting/deleting pipeline connections and (2) adding/replacing treatment units. Several case studies are presented in this thesis to demonstrate the effectiveness of proposed strategy.

    1 Introduction 1 2 Flexibility Assessment Method for Water Networks 4 2.1 Superstructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 General Design Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2.1 Primary Sources . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2.2 Secondary Sources . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.2.3 Sinks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.2.4 Processing Units . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 General Formulation of Flexibility Index Model . . . . . . . . . . . . . 8 2.4 Implementation Procedure . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.5 Additional Performance Evaluation Criterion . . . . . . . . . . . . . . . 17 3 Optimization Strategies for Flexibility Index Model 18 3.1 Smoothing Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.2 Initialization Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.3 Search Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4 Flexibility Enhancement Procedure 27 4.1 Motivation Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 4.2 Systematic Procedure to Improve Network Flexibility . . . . . . . . . . 49 5 Case Studies 51 5.1 Case I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 5.2 Case II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 5.3 Case III . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 6 Conclusions and Future Works 83 6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 6.2 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 A GAMS Code for Example 1 86

    [1] Dudley, S. (2003).Water Use in Industries of the Future: Chemical Industry. Chapter in Industrial Water Management : A Systems Approach, (2nd Edition), New York, USA.
    [2] Takama, N., Kuriyama, Y., Shiroko, K., Umeda, T. (1980). Optimal Water Allocation in a Petrochemical Re nery. Computers and Chemical Engineering, 4, pp 251-258.
    [3] Wang, Y. P., Smith, R. (1994). Wastewater Minimization. Chemical Engineering Science, 49 (7), pp 981-1006.
    [4] Alva-Argaez, A. A., Kokossis, C., Smith, R. (1998). Wastewater Minimization of Industrial System Using an Integrated Approach. Computers and Chemical Engineering, 22, pp S741-S744.
    [5] Bagajewicz, M., Rivas, M., Savelski, M. (1999). A New Approach to the Design of Utilization Systems with Multiple Contaminants in Process Plants. Annual AIChE Meeting, Dallas, TX.
    [6] Huang, C. H., Chang, C. T., Ling, H. C., Chang, C. C. (1999). A Mathematical Programming Model for Water Usage and Treatment Network Design. Industrial and Engineering Chemistry Research, 38, pp 2666-2679.
    [7] Feng, X., Seider, W. D. (2001). New Structure and Design Methodology for Water Networks. Industrial and Engineering Chemistry Research, 40, pp 6140-6146.
    [8] Karuppiah, R., I. E. Grossmann. (2006). Global Optimization for The Synthesis of Integrated Water Systems in Chemical Processes. Computers and Chemical Engineering, 30, pp. 650-673.
    [9] Tan, R. R., Cruz, D. E. (2004). Synthesis of Robust Water Reuse Networks for Single-component Retro t Problems Using Symmetric Fuzzy Linear Programming. Computers and Chemical Engineering, 28, pp 2547-2551.
    [10] Al-Redhwan, S. A., Crittenden, B. D., Lababidi, H. M. S. (2005). Wastewater Minimization Under Uncertain Operational Conditions. Computers and Chemical Engineering, 29, pp 1009-1021.
    [11] Tan, R. R., Foo, O. C. F., Manan, Z. A. (2007). Assessing The Sensitivity of Water Networks to Noisy Mass Loads Using Monte Carlo Simulation. Computers and Chemical Engineering, 31, pp 1355-1363.105
    [12] Karuppiah, R., Grossmann, I. E. (2008). Global Optimization of Multiscenario Mixed Integer Nonlinear Programming Model Arising in The Synthesis of Integrated Water Networks Under Uncertainty. Computers and Chemical Engineering, 32, pp 145-169.
    [13] Zhang, Z., Feng, X., Qian, F. (2009). Studies on Resilience of Water Networks. Chemical Engineering Journal, 147, pp 117-121.
    [14] Li, B. H., Chang, C. T., Liou, C. W. (2009). Development of a Generalized MINLP Model for Assessing and Improving The Operational Flexibility of Water Network Designs. Industrial and Engineering Chemistry Research, 48 (7), pp 3496-3504.
    [15] Swaney, R. E., and Grossmann, I. E. (1985a). An Index for Operational Flexibility in Chemical Process Design. Part I. Formulation and Theory. American Institute of Chemical Engineering Journal, 31, pp 621-630.
    [16] Swaney, R. E., and Grossmann, I. E. (1985b). An Index for Operational Flexibility in Chemical Process Design. Part II. Computational Algorithms. American Institute of Chemical Engineering Journal, 31, pp 631-641.
    [17] Grossmann, I. E., Floudas, C. A. (1987). Active Constraint Strategy for Flexibility Analysis In Chemical Processes. Computers and Chemical Engineering, 6, pp 675-693.
    [18] Bandoni, J. A., Raspanti J. G., Biegler L. T. (2000). New Strategies for Flexibility Analysis and Design under Uncertainty. Computers and Chemical Engineering, 24, pp 2193-2209.
    [19] Biegler, L. T., Balakrishna, S. (1992). Targeting Strategies for the Synthesis and Energy Integration of Non-Isothermal Reactor Networks. Industrial and Engineering Chemistry Research, 31 (9), pp 2152-2164.
    [20] Biegler, L. T., Grossmann, I. E., Westerberg, A. W. (1997). Systematic Methods of Chemical Process Design. Prentice-Hall, Inc. pp 690-714.
    [21] Clark, P. (1983). Embedded Optimization Problems in Chemical Process Design. PhD. Thesis, Carnegie Mellon University, Pittsburgh, USA.

    下載圖示 校內:2010-07-14公開
    校外:2010-07-14公開
    QR CODE