GOALI: Design and Operations of Supply Chain for Cleaner Fuels: Models, Algorithms and Implementation for Coal-fired Power Plants

目标：清洁燃料供应链的设计和运营：燃煤电厂的模型、算法和实施

• 批准号: 1660543
• 负责人: Bo Zeng
• 金额: $ 9.36万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1660543&HistoricalAwards=false
• 关键词: GOALI; Design; Operations; Supply; Chain

The research objective of this award is to establish a comprehensive characterization of fuel supply chain systems in power plants, and to develop analytical models and efficient algorithms to support them to design and operate those chains with cleaner fuels. Fuel blending has been widely adopted among coal-fired plants to produce a blend satisfying heat and emission standards, which requires power plants to manage their complex fuel chains to ensure that the right fuel is available at the right time. Such a situation is more complicated when non-traditional biomass is included for co-firing. To resolve this pressing issue, this research will: (i) collect and analyze real data to identify critical and random factors; (ii) build comprehensive fuel supply chain models using stochastic programming and/or robust optimization methods; (iii) develop efficient algorithms to compute optimal/near-optimal solutions for practical instances; (iv) demonstrate the effectiveness of those models and algorithms on achieving an optimal balance among emission reduction, economic efficiency and reliability in power generation.If successful, this research will provide a set of substantial tools that will significantly improve the design and operation of coal-fired power plants and their fuel supply chains. The estimated savings nationwide could be multi-billion dollars annually. More broadly, these tools can be utilized in biomass integration, economic analysis of retrofit technologies, and contract negotiations. They are also applicable to other industries, such as chemical and food industries. Our research findings will be disseminated timely via conferences, journal publications and a dedicated internet page containing relevant tools, models, case studies, and tutorials/manuals. Undergraduate and graduate students will also benefit from this award through new course material and research involvement. The transformative impact will be generated through the close collaboration with industrial partners and student interns.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项的研究目标是建立发电厂燃料供应链系统的全面表征，并开发分析模型和高效算法，以支持他们设计和运营使用清洁燃料的供应链。燃煤电厂广泛采用燃料混合来生产满足热量和排放标准的混合物，这要求电厂管理其复杂的燃料链，以确保在正确的时间提供正确的燃料。当包括非传统生物质用于共烧时，这种情况更加复杂。 为了解决这一紧迫问题，本研究将：（i）收集和分析真实的数据，以确定关键和随机因素;（ii）使用随机规划和/或鲁棒优化方法建立全面的燃料供应链模型;（iii）开发有效的算法，以计算实际情况下的最优/接近最优的解决方案;（iv）展示该等模型及算法在减少排放、经济效益及发电可靠性之间取得最佳平衡的成效。如成功，这项研究将提供一套实质性工具，大大改善燃煤发电厂及其燃料供应链的设计和运作。估计全国每年可节省数十亿美元。更广泛地说，这些工具可用于生物质整合、改造技术的经济分析和合同谈判。它们也适用于其他行业，如化学和食品行业。我们的研究成果将通过会议，期刊出版物和包含相关工具，模型，案例研究和教程/手册的专用网页及时传播。本科生和研究生也将通过新的课程材料和研究参与从这个奖项中受益。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。