(290f) Multi-Objective Optimization of Biorefinery and Uncertainty Analysis
The renewable energy industry is growing continuously, and it has several challenges and opportunity for research community. Biomass is a potential source of energy for future as it can be converted to transportation fuels, chemicals and electricity using bio-chemical and thermo-chemical conversion routes. Bio-alcohols production via hydrolysis and fermentation can only use cellulosic part, leaving the lignin portion as waste. On the contrary, thermo-chemical processes such as gasification and pyrolysis can use both cellulose and lignin. Gasification produces syngas which can be converted into liquid fuels, chemical and electricity. Fischerâ??Tropsch (FT) crude, methanol (MeOH) and dimethyl ether (DME) can be synthesised by syngas. Further, solid oxide fuel cell with gas turbine (SOFC-GT) has shown higher thermodynamic performance for converting syngas into electricity and particularly considering the biomass conversion integration. Decision on the best pathways highly depends on bioproducts and biofuels market prices, which are highly uncertain. Further, investment cost and price and availability of raw materials are also uncertain.
The biorefinery superstructure for this study includes following processes: gasification, SOFC-GT, FT, MeOH and DME. Design and operating conditions of this biorefinery superstructure is optimized for profit and annualized capital cost, simultaneously, using stochastic multi-objective optimization method. The final selection of a solution from the obtained Pareto-optimal front depends on its sensitivity to the uncertain parameters, such as feed and product prices, plant life and operating time. Engineers are mainly interested in selecting one or few robust solutions which are less sensitive to the uncertain parameters, and so the uncertainty analysis of the obtained non-dominated solutions may help in identifying robust solutions. In this study, effect of several uncertain operating and market parameters is studied on the performance of selected biorefinery superstructure. The uncertainty analysis is able to identify most promising biorefinery configurations, based on the profit as main decision crieriton. The results of this study will be presented at 2016 AIChE Annual Meeting.
Multi-objective Optimization, Gasification, Fischer-Tropsch Process, Methanol, Dimethyl Ether, Solid Oxide Fuel Cell, Gas Turbine, Uncertainty Analysis.
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