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Assessing solution quality and computational performance in the hydro unit commitment problem considering different mathematical programming approaches

delete2016-07-01
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PRE
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E
Erlon Cristian Finardi *
F
Fabrício Y. K. Takigawa
B
Brunno Henrique Brito
DOI:10.1016/j.epsr.2016.02.018delete
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摘要

摘要

En 中文
This paper presents a comparative analysis of different mathematical programming approaches for optimizing the hydro unit commitment (HUC) problem with cascaded plants, multiple generating units, and a head-dependent hydropower model. Regarding the HUC problem related to this paper, the objective is to minimize the cascade outflow while satisfying all constraints, including a power target for each plant, in a day-ahead planning horizon. The decision variables are the on/off status of the units and the respective generation levels. Rigorously, the HUC is a mixed-integer nonlinear programming (MINLP) problem, and several strategies can be used to compute near-optimal solutions. In this paper, we are interested in accessing the solution quality, as well as the computational performance when the HUC problem is solved using the following mathematical programming approaches: (i) the Lagrangian relaxation that represents a decomposition technique that exploits the HUC modeling structure, (ii) a MINLP solver that can handle the size and the non-concavity of the problem, and (iii) a mixed-integer linear programming (MILP) approach obtained by means of the hydropower model linearization. To perform the proposed analysis, numerical results are presented related to a real hydro system with eight cascaded reservoirs and 29 generating units. (C) 2016 Elsevier B.V. All rights reserved.
Keyword:
Hydro unit commitment
Lagrangian relaxation
Mixed-integer nonlinear programming
Mixed-integer linear programming
Hydropower model
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期刊

Electric Power Systems Research 封面图
Electric Power Systems Research
IF:
4.2
论文数:
1.2W
被引数:
2.2W

机构

I
instituto federal de santa catarina (ifsc)
学者数:
309
论文数: 256
被引数: 0
I
instituto federal catarinense
学者数:
244
论文数: 174
被引数: 0
U
universidade federal de santa catarina (ufsc)
学者数:
1.5W
论文数: 1.1W
被引数: 9
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