Symmetry issues in mixed integer programming based Unit Commitment

Alemany, Juan; Magnago, Fernando; Moitre, D.; Pinto, Herminio

doi:10.1016/j.ijepes.2013.06.034

Cited by 33 publications

(22 citation statements)

References 26 publications

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“…The existence of symmetry in UC problems has been reported in the literature in two areas: 1) benchmark problems (Morales-Espana et al, 2013;Ostrowski et al, 2012); and 2) real world generation systems (Alemany et al, 2014;Dekrajangpetch et al, 1999;Dentcheva et al, 1997).…”

Section: Symmetry In Unit Commitment Problemsmentioning

confidence: 96%

“…The e↵ects of indistinguishable generation units in UC problems has been studied before in the context of LR (Alemany et al, 2014;Benhamida and Abdelbar, 2010;Dekrajangpetch et al, 1999;Dentcheva et al, 1997;Zhai et al, 2002). In LR the symmetry was identified as a source of convergence problems, leading to suboptimal solutions or even infeasible solutions Dekrajangpetch et al (1999).…”

Section: Symmetry In Unit Commitment Problemsmentioning

confidence: 99%

“…In these problems two cases may arise: 1) processes with machines with identical characteristics (Sherali, 2001); or 2) problems where the assignment of n products has to be made to a number of m slots, with m > n . Recently Symmetry Breaking Constraints (SBC) are discussed in the context of a real world UC problem in Alemany et al (2014). The SBC implemented in that work are further discussed in Section 4.1.…”

Section: Symmetry In Unit Commitment Problemsmentioning

confidence: 99%

“…Those authors assess their method on the same set of benchmark problems used in this work. Alemany et al (2014) tested general SBC implemented in an o↵-the-shelf MILP solver against specific cuts implemented by the authors, and the former revealed to be less e cient.…”

Section: Symmetry In Unit Commitment Problemsmentioning

confidence: 99%

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Symmetry breaking in MILP formulations for Unit Commitment problems

Lima

Novais

2016

Computers & Chemical Engineering

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Please cite this article as: Ricardo M. Lima, Augusto Q. Novais, Symmetry Breaking in MILP Formulations for Unit Commitment Problems, Computers and Chemical Engineering (2015), http://dx.doi.org/10. 1016/j.compchemeng.2015.11.004 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. • Symmetry issues are discussed in the context of UC formulations.• Three sets of SBC are proposed and analyzed.• Three well-known UC MILP models are used to implement the SBC.• The results presented are completely disruptive compared with the results presented in the literature.• The SBC derived have a clear advantage over general methods available in two MILP solvers. *HighlightsPage 2 of 43 show that problems that could not be solved to optimality within hours can be solved with a relatively small computational burden if the symmetry breaking constraints are assumed.The proposed symmetry breaking constraints are also compared with the symmetry breaking methods included in two MILP solvers, and the symmetry breaking constraints derived in this work have a distinct advantage over the methods in the MILP solvers.

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Section: Symmetry In Unit Commitment Problemsmentioning

confidence: 96%

Section: Symmetry In Unit Commitment Problemsmentioning

confidence: 99%

Section: Symmetry In Unit Commitment Problemsmentioning

confidence: 99%

Section: Symmetry In Unit Commitment Problemsmentioning

confidence: 99%

See 2 more Smart Citations

Symmetry breaking in MILP formulations for Unit Commitment problems

Lima

Novais

2016

Computers & Chemical Engineering

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show abstract

“…A number of studies have been conducted over the past few decades to solve the problem including conventional analytic methods, intelligent methods, and some hybrid methods. Conventional methods such as dynamic programming (DP) [3], Lagrangian relaxation (LR) [4], branch and cut (BC) [5], Benders decomposition (BD) [6], priority list (PL) [7] as well as some other mix-integer programming solvers [8] have successfully been utilised. However, the significantly increased system complexity due to the introduction of a number of new players into the power system in recent years, such as distributed reneable generations brings considerable computational requirement on these convetional approaches, making them technically less appealing.…”

Section: Introductionmentioning

confidence: 99%