Solving unit commitment problem by combining of continuous relaxation method and genetic algorithm

Ken Ichi Tokoro; Yasushi Masuda; Hisakazu Nishino

doi:10.1109/SICE.2008.4655263

Solving unit commitment problem by combining of continuous relaxation method and genetic algorithm

Ken Ichi Tokoro, Yasushi Masuda, Hisakazu Nishino

Department of Industrial and Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 Citations (Scopus)

Abstract

This paper proposes a genetic algorithm for solving a unit commitment problem of electric generators, which formally is a mixed integer nonlinear programming problem. The proposed algorithm finds the optimal ON/OFF status of units by a combination of genetic algorithm and continuous relaxation method. In the proposed algorithm, a chromosome encodes a partial solution, in which the values of some variables are unfixed. The fitness of an individual is evaluated based upon a solution of the problem where all unfixed variables in the chromosome are relaxed to be continuous. Numerical experiments show the satisfactory performance of the proposed algorithm with respect to the solution quality for planning the actual unit commitment schedule.

Original language	English
Title of host publication	Proceedings of SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology
Pages	3474-3478
Number of pages	5
DOIs	https://doi.org/10.1109/SICE.2008.4655263
Publication status	Published - 2008
Event	SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology - Tokyo, Japan Duration: 2008 Aug 20 → 2008 Aug 22

Publication series

Name	Proceedings of the SICE Annual Conference

Other

Other	SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology
Country/Territory	Japan
City	Tokyo
Period	08/8/20 → 08/8/22

Keywords

Genetic algorithm mixed integer nonlinear optimization
Optimization
Unit commitment problem

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/SICE.2008.4655263

Cite this

Tokoro, K. I., Masuda, Y., & Nishino, H. (2008). Solving unit commitment problem by combining of continuous relaxation method and genetic algorithm. In Proceedings of SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology (pp. 3474-3478). [4655263] (Proceedings of the SICE Annual Conference). https://doi.org/10.1109/SICE.2008.4655263

Solving unit commitment problem by combining of continuous relaxation method and genetic algorithm. / Tokoro, Ken Ichi; Masuda, Yasushi; Nishino, Hisakazu.
Proceedings of SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology. 2008. p. 3474-3478 4655263 (Proceedings of the SICE Annual Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tokoro, KI, Masuda, Y & Nishino, H 2008, Solving unit commitment problem by combining of continuous relaxation method and genetic algorithm. in Proceedings of SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology., 4655263, Proceedings of the SICE Annual Conference, pp. 3474-3478, SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology, Tokyo, Japan, 08/8/20. https://doi.org/10.1109/SICE.2008.4655263

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title = "Solving unit commitment problem by combining of continuous relaxation method and genetic algorithm",

abstract = "This paper proposes a genetic algorithm for solving a unit commitment problem of electric generators, which formally is a mixed integer nonlinear programming problem. The proposed algorithm finds the optimal ON/OFF status of units by a combination of genetic algorithm and continuous relaxation method. In the proposed algorithm, a chromosome encodes a partial solution, in which the values of some variables are unfixed. The fitness of an individual is evaluated based upon a solution of the problem where all unfixed variables in the chromosome are relaxed to be continuous. Numerical experiments show the satisfactory performance of the proposed algorithm with respect to the solution quality for planning the actual unit commitment schedule.",

keywords = "Genetic algorithm mixed integer nonlinear optimization, Optimization, Unit commitment problem",

author = "Tokoro, {Ken Ichi} and Yasushi Masuda and Hisakazu Nishino",

year = "2008",

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language = "English",

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note = "SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology ; Conference date: 20-08-2008 Through 22-08-2008",

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AU - Masuda, Yasushi

AU - Nishino, Hisakazu

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AB - This paper proposes a genetic algorithm for solving a unit commitment problem of electric generators, which formally is a mixed integer nonlinear programming problem. The proposed algorithm finds the optimal ON/OFF status of units by a combination of genetic algorithm and continuous relaxation method. In the proposed algorithm, a chromosome encodes a partial solution, in which the values of some variables are unfixed. The fitness of an individual is evaluated based upon a solution of the problem where all unfixed variables in the chromosome are relaxed to be continuous. Numerical experiments show the satisfactory performance of the proposed algorithm with respect to the solution quality for planning the actual unit commitment schedule.

KW - Genetic algorithm mixed integer nonlinear optimization

KW - Optimization

KW - Unit commitment problem

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ER -

Solving unit commitment problem by combining of continuous relaxation method and genetic algorithm

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