期刊
ACS SUSTAINABLE CHEMISTRY & ENGINEERING
卷 4, 期 6, 页码 3160-3173出版社
AMER CHEMICAL SOC
DOI: 10.1021/acssuschemeng.6b00188
关键词
Two-stage adaptive robust optimization; Network optimization; Biomass; Uncertainty; MINLP
资金
- Institute for Sustainability and Energy at Northwestern University (ISEN)
- National Science Foundation (NSF) CAREER Award [CBET-1554424]
- Div Of Chem, Bioeng, Env, & Transp Sys
- Directorate For Engineering [1643244] Funding Source: National Science Foundation
A bioconversion product and process network converts different types of biomass to various fuels and chemicals via a plethora of technologies. Reliable bioconversion processing pathways should be designed considering the effect of uncertain parameters, such as biomass feedstock price and biofuel product demand. Given a large-scale bioconversion product and process network of 194 technologies and 139 materials/compounds, we propose a two-stage adaptive robust mixed-integer nonlinear programming problem. The model allows for decisions at the design and operational stages to be made sequentially and considers budgets of uncertainty to control the level of robustness. Nonlinearity in this model appears in the first-stage objective function, and the second stage problem is a linear program. We efficiently solve the proposed problem with a tailored solutions corresponding to various uncertainty budgets show that the minimum total annualized demand uncertainty compared to biomass feedstock price uncertainty.
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