Simultaneous application of predictive model and least cost formulation can substantially benefit biorefineries outside Corn Belt in United States [electronic resource] : A case study in Florida

• Ngôn ngữ: eng
• Ký hiệu phân loại: 621.48 Nuclear engineering
• Thông tin xuất bản: Washington, D.C. : Oak Ridge, Tenn. : United States. Dept. of Energy. Office of Science ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2018
• Mô tả vật lý: Size: p. 218-227 : , digital, PDF file.
• Bộ sưu tập: Metadata
• ID: 262963
• Chủ đề: 1. 09 biomass fuels; 2. Biomass blends; 3. Impact analysis; 4. Least cost formulation (lcf); 5. Predictive model

Tóm tắt

Previously, a predictive model was developed to identify optimal blends of expensive high-quality and cheaper low-quality feedstocks for a given geographical location that can deliver high sugar yields. Here, the optimal process conditions were tested for application at commercially-relevant higher biomass loadings. We observed lower sugar yields but 100% conversion to ethanol from a blend that contained only 20% high-quality feedstock. The impact of applying this predictive model simultaneously with least cost formulation model for a biorefinery location outside of the US Corn Belt in Lee County, Florida was investigated. A blend ratio of 0.30 EC, 0.45 SG, and 0.25 CS in Lee County was necessary to produce sugars at high yields and ethanol at a capacity of 50 MMGY. This work demonstrates utility in applying predictive model and LCF to reduce feedstock costs and supply chain risks while optimizing for product yields.