Energy optimization in the process industries: Unit commitment at systems level

Edwin Zondervan; Ignacio E. Grossmann; André B. de Haan

doi:10.1016/S1570-7946(10)28156-7

Energy optimization in the process industries: Unit commitment at systems level

Edwin Zondervan^*, Ignacio E. Grossmann, André B. de Haan

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › Academic › peer-review

13 Citations (Scopus)

Abstract

In previous work, the unit commitment problem has been formulated as a non-convex MINLP, which is computationally expensive to solve. To circumvent this problem, we reformulate in this paper the problem as a convex MIQCP and derive the relevant constraints using propositional logic. We consider a specific problem based on a network of gas and oil fired power generators. Numerical results are presented using several methods (e.g. CPLEX for MIQCP, and DICOPT, SBB for MINLP). It is shown that proposed convex MIQCP reformulation can be solved much faster than previous non-convex models reported in the literature.

Original language	English
Pages (from-to)	931-936
Number of pages	6
Journal	Computer Aided Chemical Engineering
Volume	28
Issue number	C
DOIs	https://doi.org/10.1016/S1570-7946(10)28156-7
Publication status	Published - 2010
Externally published	Yes
Event	20th European Symposium on Computer Aided Process Engineering, ESCAPE 2010 - Ischia, Italy Duration: 6 Jun 2010 → 9 Jun 2010 Conference number: 20

Keywords

Energy optimization
MINLP
Unit commitment problem

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/S1570-7946(10)28156-7

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title = "Energy optimization in the process industries: Unit commitment at systems level",

abstract = "In previous work, the unit commitment problem has been formulated as a non-convex MINLP, which is computationally expensive to solve. To circumvent this problem, we reformulate in this paper the problem as a convex MIQCP and derive the relevant constraints using propositional logic. We consider a specific problem based on a network of gas and oil fired power generators. Numerical results are presented using several methods (e.g. CPLEX for MIQCP, and DICOPT, SBB for MINLP). It is shown that proposed convex MIQCP reformulation can be solved much faster than previous non-convex models reported in the literature.",

keywords = "Energy optimization, MINLP, Unit commitment problem",

author = "Edwin Zondervan and Grossmann, {Ignacio E.} and {de Haan}, {Andr{\'e} B.}",

year = "2010",

doi = "10.1016/S1570-7946(10)28156-7",

language = "English",

volume = "28",

pages = "931--936",

journal = "Computer Aided Chemical Engineering",

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note = "20th European Symposium on Computer Aided Process Engineering, ESCAPE 2010, ESCAPE 2010 ; Conference date: 06-06-2010 Through 09-06-2010",

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TY - JOUR

T1 - Energy optimization in the process industries

T2 - 20th European Symposium on Computer Aided Process Engineering, ESCAPE 2010

AU - Zondervan, Edwin

AU - Grossmann, Ignacio E.

AU - de Haan, André B.

N1 - Conference code: 20

PY - 2010

Y1 - 2010

N2 - In previous work, the unit commitment problem has been formulated as a non-convex MINLP, which is computationally expensive to solve. To circumvent this problem, we reformulate in this paper the problem as a convex MIQCP and derive the relevant constraints using propositional logic. We consider a specific problem based on a network of gas and oil fired power generators. Numerical results are presented using several methods (e.g. CPLEX for MIQCP, and DICOPT, SBB for MINLP). It is shown that proposed convex MIQCP reformulation can be solved much faster than previous non-convex models reported in the literature.

AB - In previous work, the unit commitment problem has been formulated as a non-convex MINLP, which is computationally expensive to solve. To circumvent this problem, we reformulate in this paper the problem as a convex MIQCP and derive the relevant constraints using propositional logic. We consider a specific problem based on a network of gas and oil fired power generators. Numerical results are presented using several methods (e.g. CPLEX for MIQCP, and DICOPT, SBB for MINLP). It is shown that proposed convex MIQCP reformulation can be solved much faster than previous non-convex models reported in the literature.

KW - Energy optimization

KW - MINLP

KW - Unit commitment problem

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U2 - 10.1016/S1570-7946(10)28156-7

DO - 10.1016/S1570-7946(10)28156-7

M3 - Conference article

AN - SCOPUS:78651413704

SN - 1570-7946

VL - 28

SP - 931

EP - 936

JO - Computer Aided Chemical Engineering

JF - Computer Aided Chemical Engineering

IS - C

Y2 - 6 June 2010 through 9 June 2010

ER -

Energy optimization in the process industries: Unit commitment at systems level

Abstract

Keywords

UN SDGs

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