Optimizing model complexity with application to fuel cell based power systems

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.

[1]  Tohru Kato,et al.  Numerical analysis of output characteristics of tubular SOFC with internal reformer , 2001 .

[2]  Urmila M. Diwekar,et al.  Multi-objective optimization for hybrid fuel cells power system under uncertainty , 2004 .

[3]  Urmila M. Diwekar,et al.  An Efficient Sampling Approach to Multiobjective Optimization , 2004, Ann. Oper. Res..

[4]  Said Al-Hallaj,et al.  A novel design for solid oxide fuel cell stacks , 2004 .

[5]  Edward S. Rubin,et al.  Optimal design of advanced power systems under uncertainty , 1997 .

[6]  Anil V. Virkar,et al.  The role of electrode microstructure on activation and concentration polarizations in solid oxide fuel cells , 2000 .

[7]  Marc A. Rosen,et al.  Modelling and analysis of a solid polymer fuel cell system for transportation applications , 2001 .

[8]  Stefano Campanari,et al.  Thermodynamic model and parametric analysis of a tubular SOFC module , 2001 .

[9]  Kus Hidajat,et al.  Simulation of a solid oxide fuel cell for oxidative coupling of methane , 1999 .

[10]  F. R. Foulkes,et al.  Fuel Cell Handbook , 1989 .

[11]  R. G. Colclaser,et al.  Transient modeling and simulation of a tubular solid oxide fuel cell , 1999 .

[12]  Urmila M. Diwekar,et al.  Characterization and quantification of uncertainty in solid oxide fuel cell hybrid power plants , 2005 .

[13]  Urmila M. Diwekar,et al.  An efficient sampling technique for off-line quality control , 1997 .

[14]  S. Chan,et al.  A complete polarization model of a solid oxide fuel cell and its sensitivity to the change of cell component thickness , 2001 .

[15]  L. Kershenbaum,et al.  Modelling of an indirect internal reforming solid oxide fuel cell , 2002 .

[16]  S. Cocchi,et al.  A global thermo-electrochemical model for SOFC systems design and engineering , 2003 .

[17]  G. Maggio,et al.  Modeling polymer electrolyte fuel cells: an innovative approach , 2001 .

[18]  Urmila M. Diwekar,et al.  Introduction to Applied Optimization , 2020, Springer Optimization and Its Applications.