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Sequential Lagrangian-MILP approaches for Unit Commitment problems

delete2011-03-01
delete58
PRE
AI
A
Antonio Frangioni
C
Claudio Gentile *
F
F. Lacalandra
DOI:10.1016/j.ijepes.2010.12.013delete
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摘要

摘要

En 中文
The short-term Unit Commitment (UC) problem in hydro-thermal power generation is a fundamental problem in short-term electrical generation scheduling. Historically, Lagrangian techniques have been used to tackle this large-scale, difficult Mixed-Integer NonLinear Program (MINLP); this requires being able to efficiently solve the Lagrangian subproblems, which has only recently become possible (efficiently enough) for units subject to significant ramp constraints. In the last years, alternative approaches have been devised where the nonlinearities in the problem are approximated by means of piecewise-linear functions, so that UC can be approximated by a Mixed-Integer Linear Program (MILP); in particular, using a recently developed class of valid inequalities for the problem, called Perspective Cuts, significant improvements have been obtained in the efficiency and effectiveness of the solution algorithms. These two different approaches have complementary strengths; Lagrangian ones provide very good lower bounds quickly, but they require sophisticated heuristics which may need to be changed every time that the mathematical model changes for producing actual feasible solutions. MILP approaches have been shown to be able to provide very good feasible solutions quickly, but their lower bound is significantly worse. We present a sequential approach which combines the two method;, trying to exploit each ones strengths; we show, by means of extensive computational experiments on realistic instances, that the sequential approach may exhibit significantly better efficiency than either of the two basic ones, depending on the degree of accuracy requested to the feasible solutions. (c) 2011 Elsevier Ltd. All rights reserved.
Keyword:
OR in energy
Hydro-thermal Unit Commitment
Mixed-integer nonlinear program formulations
Lagrangian Relaxation

期刊

I
International Journal of Electrical Power and Energy Systems
IF:
5
论文数:
1.1W
被引数:
3.1W

机构

U
University of Pisa
学者数:
3.1W
论文数: 2.4W
被引数: 2.4W
C
consiglio nazionale delle ricerche (cnr)
学者数:
6.2W
论文数: 5.7W
被引数: 48
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