文献类型：期刊文献

英文题名：Production of α-olefins from biomass gasification: Process development and multi-objective optimization for techno-economic and environmental goals

作者：Xi, Chuandong[1];Fu, Kaihao[1];Cao, Chenxi[2];Yang, Zixu[1];Han, Yi-Fan[1,3]

机构：[1]East China Univ Sci & Technol, State Key Lab Chem Engn, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[3]Zhengzhou Univ, Engn Res Ctr Adv Funct Mat Mfg, Minist Educ, Zhengzhou 450001, Peoples R China

年份：2024

卷号：11

外文期刊名：CARBON CAPTURE SCIENCE & TECHNOLOGY

收录：WOS:【ESCI(收录号:WOS:001200178500001)】；

基金：Acknowledgments The authors greatly acknowledge the funding support from Na-tional Natural Science Funds of China (NSFC22238003, 22378118, 22278405) and Open Fund of State Key Laboratory of Chemical Engi-neering (GZA01220102) .

语种：英文

外文关键词：Process simulation; Biomass gasification; Multi-objective optimization; Heat integration; Factor analysis

摘要：Efficient utilization of biomass as a substitute for fossil fuels holds great promise for meeting future greener chemical demands in a sustainable manner. This study presents a process simulation and multi-objective optimization for an innovative process of biomass-based Fischer-Tropsch synthesis of value-added linear alpha-olefins. Optimal design and operation solutions with heat-exchange network integration taken into account are obtained that minimize total annual costs (TAC), generalized energy consumption ( GEC ), greenhouse gas emissions (GHG), and maximize product yields (eta). Compared to the benchmark case, this optimization leads to a 9.93 % reduction in TAC, a 21.76 % reduction in GEC , a 19.23 % reduction in GHG, and increases eta by 1.41 %. Additionally, a comprehensive factor analysis of the optimal design and operation parameters in the Pareto front helps to discover patterns related to energy consumption, environmental impact, or economy. This allows to maximize a specific key process performance metric while minimizing the loss in the other, thus enabling flexible process design and operation under diverse manufacturing environments.