基于 MINLP 的决策工具,帮助微型酿酒厂通过改造提高能效并减少碳足迹

IF 3 Q2 ENGINEERING, CHEMICAL Digital Chemical Engineering Pub Date : 2024-10-03 DOI:10.1016/j.dche.2024.100189
Veit Schagon, Rohit Murali, Ruosi Zhang, Melis Duyar, Michael Short
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引用次数: 0

摘要

与大型啤酒厂相比,微型啤酒厂每升啤酒的生产成本更高,碳足迹也更大。由于现有的改造技术多种多样,而且微型啤酒厂的产能和配置也各不相同,因此并不总是很清楚什么样的改造才能改善运营。因此,这项工作提出了一种新颖的混合整数非线性编程决策工具,可供任何微型酿酒厂使用,用于确定提高能效改造的技术经济可行性和规模,包括太阳能和风能、电池存储、厌氧消化、锅炉类型选择、通过热存储进行热集成以及通过双功能材料进行碳捕集。该模型在一个真实的英国微型酿酒厂案例研究中进行了演示。该模型给出了一个 10 立方米厌氧消化器、30 块太阳能电池板(每块输出功率为 380 瓦)、800 瓦风力涡轮机和 2.3 立方米储热罐的最佳配置,每年可降低 62.9% 的运营成本和 77.1% 的二氧化碳排放量,投资回收期为 8 年。该工具设计灵活,适用于任何地点、任何酿造配方的任何微型啤酒厂,使所有者都能开发出利润更高、更可持续的微型啤酒厂。
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An MINLP-based decision-making tool to help microbreweries improve energy efficiency and reduce carbon footprint through retrofits
Microbreweries have greater production costs per litre of beer compared to large breweries, as well as higher carbon footprints. Due to the range of different retrofit technologies available and the different capacities and configurations of microbreweries, it is not always clear what retrofits will improve operations. Therefore, this work proposes a novel mixed-integer nonlinear programming decision-making tool to be used by any microbrewery, that determines the technoeconomic feasibility and sizing of energy efficiency-improving retrofits, including solar and wind power, battery storage, anaerobic digestion, boiler type selection, heat integration by heat storage, and carbon capture via dual-function materials. The model was demonstrated on a real UK microbrewery case study. The model gave an optimal configuration of a 10 m3 anaerobic digester, 30 solar panels outputting 380 W each, an 800 W wind turbine and a 2.3 m3 heat storage tank, reducing annual operating costs by 62.9 % and carbon dioxide emissions by 77.1 % with a payback period of 8 years. The tool is designed to be flexible for use by any microbrewery in any location with any brewing recipe and allow the owner(s) to develop more profitable and sustainable microbreweries.
Tweetable abstract
Microbreweries can implement mathematically optimised renewable energy, heat integration and anaerobic digestion to reduce operating costs by 62.9 % and carbon emissions by 77.1 %.
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