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Incorporating agricultural waste-to-energy pathways into biomass product and process network through data-driven nonlinear adaptive robust optimization

机译:通过数据驱动的非线性自适应稳健优化将农业废物到能量通路纳入生物质产品和过程网络中

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摘要

A biomass product and process network that displays how organic waste and other non-traditional biomass feedstocks may be converted into useful bioproducts and biofuels is a necessary addition to the field of biomass conversion and utilization. We develop a processing network of 216 technologies and 172 materials/compounds that contains conversion pathways of agricultural and organic waste biomass sources, such as food peels, animal manure, and grease. To examine the effectiveness and economic feasibility of these conversion pathways, the biomass product and process network is optimized for return on investment. The resulting problem is a data-driven two-stage adaptive robust mixed-integer nonlinear fractional program, which was effectively solved via a tailored optimization algorithm. The proposed approach is applied to two case studies in which traditional agricultural feedstocks are used alongside biological and agricultural waste feedstocks. The selected feedstocks were used to satisfy and, in some cases, even exceed demand for selected products. The optimal pathways have returns on investment of 26.1% and 6.2%, with utilized conversion technologies ranging from hydrocracking to microwave hydrodiffusion. In both cases, we find that profitable processing pathways are utilized at maximum capacities to increase return on investment. Specifically, in the case study where orange peel wastes are used to produce pectin, we find that this pathway is highly profitable at the given market price. The two cases that are run using the proposed model are then compared to additional cases to display differences that arise when uncertainty is not considered and the objective function of the model is changed. (C) 2019 Elsevier Ltd. All rights reserved.
机译:一种展示有机废物和其他非传统生物质原料的过程和过程网络可以转化为有用的生物制作和生物燃料是生物质转化和利用领域的必要补充。我们开发了216种技术和172种材料/化合物的处理网络,其中包含农业和有机废物生物质来源的转化途径,例如食物皮,动物粪和油脂。为了检查这些转化途径的有效性和经济可行性,生物量产品和过程网络被优化以获得投资回报。结果问题是数据驱动的两级自适应稳健混合整数非线性分数程序,其通过定制优化算法有效地解决。该方法适用于两种案例研究,其中传统农业原料与生物和农业废料原料一起使用。选定的原料用于满足,在某些情况下,甚至超过所选产品的需求。最佳途径有26.1%和6.2%的投资回报,利用转换技术,从加氢裂化到微波氢化物。在这两种情况下,我们发现利用盈利加工途径以增加投资回报的最大能力。具体而言,在橙皮废物用于产生果胶的情况下,我们发现该途径在给定的市场价格上很有利可图。然后将使用所提出的模型运行的两个案例与额外的情况进行比较,以显示不考虑不确定性时出现的差异,并且改变了模型的目标函数。 (c)2019 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Energy》 |2019年第1期|556-571|共16页
  • 作者单位

    Cornell Univ Robert Frederick Smith Sch Chem & Biomol Engn Ithaca NY 14853 USA|Cornell Univ Sch Operat Res & Informat Engn Ithaca NY 14853 USA;

    Cornell Univ Robert Frederick Smith Sch Chem & Biomol Engn Ithaca NY 14853 USA;

    Cornell Univ Robert Frederick Smith Sch Chem & Biomol Engn Ithaca NY 14853 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Adaptive robust optimization; Return on investment; Biomass conversion; Machine learning;

    机译:自适应稳健优化;投资回报;生物量转换;机器学习;

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