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Integration of Energy-cost Optimization and Production Scheduling Using Multiparametric Programming
KTH.
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2016 (English)In: Computer Aided Chemical Engineering, Elsevier, 2016, 559-564 p.Conference paper, (Refereed)
Abstract [en]

In energy-intensive industries, the traditional strategy is to schedule the production first. From the production schedule, the demand for energy is predicted and an optimization of the energy-supply cost is performed. The academic approach is to combine all the production and energy-cost related constraints into a single monolithic problem. In contrast, in this work a different approach is proposed. The energy-cost optimization problem is solved using Multiparametric Programming (mp), separately from the scheduling problem. Based on the solution from the mp-MILP (Mixed Integer Linear Programming) problem, several production scheduling problems with sensitivity information from the mp-MILP solution embedded can be solved in parallel in order to find the system-optimal solution. The approach is tested on realistic data instances of a stainless-steel process and obtains the optimal solution. However, the computational performance is strongly limited to very small instances due to limitations of the mp-MILP solvers.

Place, publisher, year, edition, pages
Elsevier, 2016. 559-564 p.
Keyword [en]
energy cost optimization, Multiparametric Programming, production scheduling, stainless-steel
National Category
Energy Engineering Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:kth:diva-201999DOI: 10.1016/B978-0-444-63428-3.50098-9Scopus ID: 2-s2.0-84994275739ISBN: 9780444634283 (print)OAI: oai:DiVA.org:kth-201999DiVA: diva2:1077037
Note

QC 20170224

Available from: 2017-02-24 Created: 2017-02-24 Last updated: 2017-02-24Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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