Decision-making in fuel ethanol production faces many uncertainties arising from raw material and product price fluctuations, and process parameter changes. This study analyzes how to reduce the costs and improve the overall efficiency even with these system uncertainties using two types of system uncertainty optimization models with these factors. The research uses a cellulosic ethanol system as a sample case to analyze the design margin problems in the design phase and the raw-material structural problems in the operating phase. The analysis uses stochastic chance-constrained programming model. The results show that uncertainty optimization is more reasonable than certainty optimization, and that the model can reduce costs as well as enhance the system risk resistance.
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2014, Vol. 54 
),陈定江1,沈静珠1,杜风光2
