Distributed power generation is one of the most powerful applications of fuel cell technology. Several types of configurations have been hypothesized and tested for these kinds of applications at the conceptual level, but hybrid power plants are one of the most efficient. These are designs that combine the fuel cell cycle with other thermodynamic cycles to provide higher efficiency. The power plant in focus is the high pressure (HP)–low pressure (LP) solid oxide fuel cells (SOFC)/steam turbine (ST)/gas turbine (GT) configuration which is a part of the vision-21 program, which is a new approach, the U.S. Department of Energy's (DOE's) Office of Fossil Energy has begun, for developing 21st century energy plants that would have virtually no environmental impact. The overall goal is to effectively eliminate—at competitive costs—environmental concerns associated with the use of fossil fuels, for producing electricity and transportation fuels. In this design, coal is gasified in an entrained bed gasifier and the syn-gas produced is cleaned in a transport bed desulfurizer and passed over to cascaded SOFC modules (at two pressure levels). This module is integrated with a reheat GT cycle. The heat of the exhaust from the GT cycle is used to convert water to steam, which is eventually used in a steam bottoming cycle. Since this hybrid technology is new and futuristic, the system level models used for predicting the fuel cells’ performance and for other modules like the desulfurizer have significant uncertainties in them. Also, the performance curves of the SOFC would differ depending on the materials used for the anode, cathode and electrolyte. The accurate characterization and quantification of these uncertainties is crucial for the validity of the model predictions and hence is the main focus of this paper. This work performs a two-level uncertainty analysis of the fuel cell module: uncertainty associated with (1) model and (2) material used for anode, cathode and electrolytes. Following that the paper deals with the uncertainty analysis of the desulfurization reaction module based in particular on the activation energy and frequency factors for different sorbents used. This paper lays the basis for two analyses: (1) the effect of uncertainties on the trade-off surface obtained through a multi-objective optimization framework; (2) development of the “value of research” framework which is concerned with analyzing the trade-offs between allocation of resources for the reduction of uncertainties and benefits accrued to the objectives through this reduction [K. Subramanyan, U. Diwekar, The ‘value of research’ methodology applied to the solid oxide fuel cell/steam turbine/gas turbine hybrid power plant design, Ind. Eng. Chem. Res., submitted for publication].
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