Evaluation of two lagrangian dual optimization algorithms for large-scale unit commitment problems

Wen Fan; Yuan Liao; Jong Beom Lee; Yong Kab Kim

doi:10.5370/JEET.2012.7.1.17

Evaluation of two lagrangian dual optimization algorithms for large-scale unit commitment problems

Wen Fan
, Yuan Liao
, Jong Beom Lee
, Yong Kab Kim

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Lagrangian relaxation is the most widely adopted method for solving unit commitment (UC) problems. It consists of two steps: dual optimization and primal feasible solution construction. The dual optimization step is crucial in determining the overall performance of the solution. This paper intends to evaluate two dual optimization methods - one based on subgradient (SG) and the other based on the cutting plane. Large-scale UC problems with hundreds of thousands of variables and constraints have been generated for evaluation purposes. It is found that the evaluated SG method yields very promising results.

Original language	English
Pages (from-to)	17-22
Number of pages	6
Journal	Journal of Electrical Engineering and Technology
Volume	7
Issue number	1
DOIs	https://doi.org/10.5370/JEET.2012.7.1.17
State	Published - Jan 2012

Keywords

Dual optimization
Lagrangian relaxation
Resource scheduling
Unit commitment

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.5370/JEET.2012.7.1.17

Cite this

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abstract = "Lagrangian relaxation is the most widely adopted method for solving unit commitment (UC) problems. It consists of two steps: dual optimization and primal feasible solution construction. The dual optimization step is crucial in determining the overall performance of the solution. This paper intends to evaluate two dual optimization methods - one based on subgradient (SG) and the other based on the cutting plane. Large-scale UC problems with hundreds of thousands of variables and constraints have been generated for evaluation purposes. It is found that the evaluated SG method yields very promising results.",

keywords = "Dual optimization, Lagrangian relaxation, Resource scheduling, Unit commitment",

author = "Wen Fan and Yuan Liao and Lee, \{Jong Beom\} and Kim, \{Yong Kab\}",

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AU - Liao, Yuan

AU - Lee, Jong Beom

AU - Kim, Yong Kab

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Y1 - 2012/1

N2 - Lagrangian relaxation is the most widely adopted method for solving unit commitment (UC) problems. It consists of two steps: dual optimization and primal feasible solution construction. The dual optimization step is crucial in determining the overall performance of the solution. This paper intends to evaluate two dual optimization methods - one based on subgradient (SG) and the other based on the cutting plane. Large-scale UC problems with hundreds of thousands of variables and constraints have been generated for evaluation purposes. It is found that the evaluated SG method yields very promising results.

AB - Lagrangian relaxation is the most widely adopted method for solving unit commitment (UC) problems. It consists of two steps: dual optimization and primal feasible solution construction. The dual optimization step is crucial in determining the overall performance of the solution. This paper intends to evaluate two dual optimization methods - one based on subgradient (SG) and the other based on the cutting plane. Large-scale UC problems with hundreds of thousands of variables and constraints have been generated for evaluation purposes. It is found that the evaluated SG method yields very promising results.

KW - Dual optimization

KW - Lagrangian relaxation

KW - Resource scheduling

KW - Unit commitment

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JO - Journal of Electrical Engineering and Technology

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ER -

Evaluation of two lagrangian dual optimization algorithms for large-scale unit commitment problems

Abstract

Keywords

ASJC Scopus subject areas

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