参考工作点的集中生产计划:在化石燃料发电厂的应用

IF 1.1 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
S. Lozano, I. Contreras
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引用次数: 0

摘要

摘要本文提出了一种集中式数据包络分析(DEA)方法,用于在给定期望的总生产目标的情况下确定组织中不同工厂的有效工作点。所提出的方法使总投入消耗和不良产出产生最小化。引入了每个工厂参考工作点的概念,并将其用于多目标问题的尺度化以及锚定每个工厂计算的目标。此外,还建立了DEA模型,以检验总生产目标的可行性,并衡量每个工厂的剩余闲置产能。该方法已被应用于美国一家大型公用事业公司旗下化石燃料发电厂的电力结构和污染物排放。考虑了总发电量减少5%的情景,以及每个工厂总发电量的+/ - 20%界限。结果表明,在对所有污染物给予同等重视的情况下,CO2和Hg分别减少6%和9%,SO2和NOx减少35%以上。通过集中生产计划获得的减排量要大于单个工厂独立确定自己的生产计划所能实现的减排量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Centralized production planning using reference operating points: application to fossil fuel power plants
Abstract This article proposes a centralized Data Envelopment Analysis (DEA) approach for determining efficient operation points for the different plants of an organization given the desired aggregate production targets. The proposed approach minimizes the total input consumption and undesirable output generation. The concept of a reference operating point for each plant is introduced and used to scalarize the multiobjective problem as well as to anchor the targets computed for each plant. Additional DEA models to check the feasibility of the aggregate production targets and to gauge remaining slack capacity for each plant are also formulated. The proposed approach has been applied to the electricity mix and pollutant emissions of fossil fuel power plants owned by a large US utility. A scenario of 5% reduction in the aggregate electricity production has been considered together with +/−20% bounds on the total electricity produced by each plant. The results indicate that, giving the same importance to all pollutants, reductions of 6% and 9% for CO2 and Hg, respectively, and above 35% for SO2 and NOx can be achieved. These emissions reductions obtained by centralized production planning are larger than those that can be achieved by the individual plants independently determining their own production plans.
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来源期刊
Infor
Infor 管理科学-计算机:信息系统
CiteScore
2.60
自引率
7.70%
发文量
16
审稿时长
>12 weeks
期刊介绍: INFOR: Information Systems and Operational Research is published and sponsored by the Canadian Operational Research Society. It provides its readers with papers on a powerful combination of subjects: Information Systems and Operational Research. The importance of combining IS and OR in one journal is that both aim to expand quantitative scientific approaches to management. With this integration, the theory, methodology, and practice of OR and IS are thoroughly examined. INFOR is available in print and online.
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