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A multidisciplinary techno-economic decision support tool for validating long-term economic viability of biorefining processes

机译:一种多学科的技术经济决策支持工具,用于验证生物精制过程的长期经济可行性

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摘要

Increasing demand for energy and transportation fuel has motivated researchers all around the world to explore alternatives for a long-term sustainable source of energy. Biomass is one such renewable resource that can be converted into various marketable products by the process of biorefining. Currently, research is taking strides in developing conversion techniques for producing biofuels from multiple bio-based feedstocks. However, the greatest concern with emerging processes is the long-term viability as a sustainable source of energy. Hence, a framework is required that can incorporate novel and existing processes to validate their economic, environmental and social potential in satisfying present energy demands, without compromising the ability of future generations to meet their own energy needs.;This research focuses on developing a framework that can incorporate fundamental research to determine its long-term viability, simultaneously providing critical techno-economic and decision support information to various stakeholders. This contribution links various simulation and optimization models to create a decision support tool, to estimate the viability of biorefining options in any given region. Multiple disciplines from the Process Systems Engineering and Supply Chain Management are integrated to develop the comprehensive framework. Process simulation models for thermochemical and biochemical processes are developed and optimized using Aspen Engineering Suite. Finally, for validation, the framework is analyzed by combining the outcomes of the process simulation with the supply chain models. The developed techno-economic model takes into account detailed variable costs and capital investments for various conversion processes. Subsequently, case studies are performed to demonstrate the applicability of the decision support tool for the Jackson Purchase region of Western Kentucky. The multidisciplinary framework is a unique contribution in the field of Process Systems Engineering as it demonstrates simulation of process optimization models and illustrates its iterative linking with the supply chain optimization models to estimate the economics of biorefinery from multistakeholder perspective. This informative tool not only assists in comparing modes of operation but also forecasts the effect of future scenarios, such as, utilization of marginal land for planting dedicated energy crops and incorporation of emerging enzymatic processes. The resulting framework is novel and informative in assisting investors, policy makers and other stakeholders for evaluating the impacts of biorefining. The results obtained supports the generalizability of this tool to be applied in any given region and guide stakeholders in making financial and strategic decisions.;KEYWORDS: Biorefining Supply Chains, Biofuels, Lignocellulosic Biomass, Sustainability, Strategic Decision Support Tool.
机译:对能源和运输燃料的需求不断增长,促使世界各地的研究人员为长期可持续的能源探索替代方案。生物质就是这样一种可再生资源,可以通过生物精炼过程将其转化为各种可销售的产品。当前,研究正在开发用于从多种生物基原料生产生物燃料的转化技术方面取得长足进展。但是,新兴工艺最令人担忧的是作为可持续能源的长期可行性。因此,需要一个框架,该框架可以结合新颖的过程和现有过程,以验证其在满足当前能源需求方面的经济,环境和社会潜力,同时又不损害子孙后代满足其自身能源需求的能力。可以结合基础研究来确定其长期可行性,同时为各种利益相关者提供关键的技术经济和决策支持信息。该贡献链接了各种模拟和优化模型,以创建决策支持工具,以评估任何给定区域中生物精炼方案的可行性。来自过程系统工程和供应链管理的多个学科被整合以开发综合框架。使用Aspen Engineering Suite开发并优化了热化学和生化过程的过程模拟模型。最后,为了进行验证,通过将过程仿真的结果与供应链模型相结合来分析框架。发达的技术经济模型考虑了各种转化过程的详细可变成本和资本投资。随后,进行了案例研究,以证明决策支持工具在西肯塔基州杰克逊购买地区的适用性。多学科框架是过程系统工程领域的独特贡献,因为它演示了过程优化模型的仿真,并说明了其与供应链优化模型的迭代联系,以便从多利益相关方的角度评估生物炼油厂的经济性。该信息工具不仅有助于比较操作模式,还可以预测未来情景的影响,例如利用边际土地种植专用能源作物和纳入新兴的酶促工艺。由此产生的框架新颖而有用,可帮助投资者,决策者和其他利益相关者评估生物炼制的影响。获得的结果支持该工具可在任何给定区域应用,并指导利益相关者制定财务和战略决策。关键词:生物炼制供应链,生物燃料,木质纤维素生物质,可持续性,战略决策支持工具。

著录项

  • 作者

    Sukumara, Sumesh.;

  • 作者单位

    University of Kentucky.;

  • 授予单位 University of Kentucky.;
  • 学科 Chemical engineering.;Operations research.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 203 p.
  • 总页数 203
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:40:45

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