Integration of different models in the design of chemical processes: Application to the design of a power plant

被引:19
作者
Caballero, Jose A. [1 ]
Navarro, Miguel A. [1 ]
Ruiz-Femenia, Ruben [1 ]
Grossmann, Ignacio E. [2 ]
机构
[1] Univ Alicante, Dept Chem Engn, E-03080 Alicante, Spain
[2] Carnegie Mellon Univ, Dept Chem Engn, Pittsburgh, PA 15213 USA
关键词
Process synthesis; Generalized Disjunctive Programming; Utility systems; Modular optimization; Kriging; MIXED-INTEGER; CONCEPTUAL OPTIMIZATION; STRUCTURAL OPTIMIZATION; FLOWSHEET OPTIMIZATION; OPERATIONAL VARIATIONS; GLOBAL OPTIMIZATION; MINLP OPTIMIZATION; UTILITY NETWORKS; ALGORITHM; STRATEGY;
D O I
10.1016/j.apenergy.2014.03.018
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With advances in the synthesis and design of chemical processes there is an increasing need for more complex mathematical models with which to screen the alternatives that constitute accurate and reliable process models. Despite the wide availability of sophisticated tools for simulation, optimization and synthesis of chemical processes, the user is frequently interested in using the 'best available model'. However, in practice, these models are usually little more than a black box with a rigid input output structure. In this paper we propose to tackle all these models using generalized disjunctive programming to capture the numerical characteristics of each model (in equation form, modular, noisy, etc.) and to deal with each of them according to their individual characteristics. The result is a hybrid modular equation based approach that allows synthesizing complex processes using different models in a robust and reliable way. The capabilities of the proposed approach are discussed with a case study: the design of a utility system power plant that has been decomposed into its constitutive elements, each treated differently numerically. And finally, numerical results and conclusions are presented. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:256 / 273
页数:18
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