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A robust optimisation approach for identifying multi-state collaborations to reduce CO_2 emissions

机译:一种稳健的优化方法,用于识别多州合作以减少CO_2排放

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摘要

Co-firing woody biomass with coal is one approach electricity providers can take to achieve emissions reductions without significantly modifying their existing infrastructure. An important aspect of EPA recommendations for reducing carbon emissions from coal-fired power plants is an allowance for states to enter into multi-state compliance partnerships. This study presents mixed integer linear programming models to identify min-cost approaches for reducing carbon emissions via biomass co-firing subject to spatially-explicit biomass availability constraints, utilising a robust optimisation approach to address uncertainties in costs and emission rates. We apply these models to a set of 18 states in the Northern US, to demonstrate how one state could identify efficient sets of multi-state collaborators.
机译:与煤炭共同燃烧的木质生物质是一种接受电力提供商,可以采取措施来实现排放减少,而不会显着修改其现有的基础设施。 EPA关于减少燃煤发电厂碳排放的EPA建议的一个重要方面是各国进入多国遵守伙伴关系的津贴。本研究介绍了混合整数线性规划模型,以识别通过生物质共射来减少碳排放的最小成本方法,这些方法在空间显式生物量可用性约束,利用稳健的优化方法来应对成本和排放率的不确定性。我们将这些模型应用于美国北部的一组18个州,以展示一个国家如何识别有效的多州合作者。

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