Optimizing model complexity with application to fuel cell based power systems

被引：17

作者：

Subramanyan, Karthik ^{[1
]}

Diwekar, Urmila M. ^{[1
]}

机构：

[1] Vishwamitra Res Inst, Ctr Uncertain Syst Tools Optimizat & Management, Westmont, IL 60607 USA

来源：

CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION | 2007年 / 46卷 / 11期

关键词：

reduced order model; optimal model complexity; SOFC; PEMFC; fuel cell based power system;

D O I：

10.1016/j.cep.2007.02.032

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：

Chemical process simulators employ two levels of models: (1) a forest level description of models and (2) a more detailed tree level description. Reducing model order is beneficial for reducing computational complexity. However, this increases uncertainties in model prediction. This paper presents a methodology based on multi-objective optimization to find optimal model complexity in the face of model uncertainties. A case study of fuel cell power plant is presented where different level models for SOFC and PEMFC are evaluated. (c) 2007 Elsevier B. V. All rights reserved.

引用

页码：1116 / 1128

页数：13

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