4.6 Article

Moving horizon closed-loop production scheduling using dynamic process models

期刊

AICHE JOURNAL
卷 63, 期 2, 页码 639-651

出版社

WILEY-BLACKWELL
DOI: 10.1002/aic.15408

关键词

closed-loop scheduling; moving horizon; rescheduling; dynamic constraints

资金

  1. National Science Foundation (NSF) through the CAREER [1454433, CBET-1512379]
  2. ABB Corporate Research through the NSF Industry/University Cooperative Research Center on Next Generation Photovoltaics [IIP-1134849]
  3. Doctoral Fellowship Award of the Cockrell School of Engineering at The University of Texas at Austin
  4. STAR Fellowship by the U.S. Environmental Protection Agency (EPA) [F13A10018]
  5. Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China
  6. EPA [673532, F13A10018] Funding Source: Federal RePORTER
  7. Directorate For Engineering
  8. Div Of Chem, Bioeng, Env, & Transp Sys [1512379] Funding Source: National Science Foundation

向作者/读者索取更多资源

The economic circumstances that define the operation of chemical processes (e.g., product demand, feedstock and energy prices) are increasingly variable. To maximize profit, changes in production rate and product grade must be scheduled with increased frequency. To do so, process dynamics must be considered in production scheduling calculations, and schedules should be recomputed when updated economic information becomes available. In this article, this need is addressed by introducing a novel moving horizon closed-loop scheduling approach. Process dynamics are represented explicitly in the scheduling calculation via low-order models of the closed-loop dynamics of scheduling-relevant variables, and a feedback connection is built based on these variables using an observer structure to update model states. The feedback rescheduling mechanism consists of, (a) periodic schedule updates that reflect updated price and demand forecasts, and, (b) event-driven updates that account for process and market disturbances. The theoretical developments are demonstrated on the model of an industrial-scale air separation unit. (c) 2016 American Institute of Chemical Engineers AIChE J, 63: 639-651, 2017

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