Synthesis/design optimization of SOFC–PEM hybrid system under uncertainty

Solid oxide fuel cell–proton exchange membrane (SOFC–PEM) hybrid system is being foreseen as a valuable alternative for power generation. As this hybrid system is a conceptual design, many uncertainties involving input values should be considered at the early stage of process optimization. We present in this paper a generalized framework of multi-objective optimization under uncertainty for the synthesis/design optimization of the SOFC–PEM hybrid system. The framework is based on geometric, economic and electrochemical models and focuses on evaluating the effect of uncertainty in operating parameters on three conflicting objectives: electricity efficiency, SOFC current density and capital cost of system. The multi-objective optimization provides solutions in the form of a Pareto surface, with a range of possible synthesis/design solutions and a logical procedure for searching the global optimum solution for decision maker. Comparing the stochastic and deterministic Pareto surfaces of different objectives, we conclude that the objectives are considerably influenced by uncertainties because the two trade-off surfaces are different.

In the SOFC–PEMFC hybrid system, the SOFC stack produces power together with an exhaust stream containing unused CO and H2. After the removal of the CO, the rich-hydrogen gas is fed to the PEMFC to generate additional power. For this novel power system, there are significant uncertainties and inaccuracies in the system design, plant operation, and cost estimates. The stochastic multi-objective optimizer approach is used to develop a synthesis/design optimization for the SOFC–PEM hybrid system, investigate the effects of operating uncertainties on the objectives by comparing the stochastic and deterministic Pareto surfaces, and determine the optimum values of decision variables.Figure optionsDownload as PowerPoint slide