Genetic-based unit commitment algorithm

Author

Maifeld, Tim T. ; Sheble, Gerald B.

Author_Institution

Dept. of Electr. Eng., Iowa State Univ., Ames, IA, USA

Volume

11

Issue

3

fYear

1996

fDate

8/1/1996 12:00:00 AM

Firstpage

1359

Lastpage

1370

Abstract

This paper presents a new unit commitment scheduling algorithm. The proposed algorithm consist of using a genetic algorithm with domain specific mutation operators. The proposed algorithm can easily accommodate any constraint that can be true costed. Robustness of the proposed algorithm is demonstrated by comparison to a Lagrangian relaxation unit commitment algorithm on three different electric utilities. Results show the proposed algorithm finds good unit commitment schedules in a reasonable amount of computation time. Included in the appendix is an explanation of the true costing approach

Keywords

costing; economics; genetic algorithms; load dispatching; load distribution; numerical stability; power system planning; scheduling; Lagrangian relaxation; computation time; domain specific mutation operators; electric utilities; genetic algorithm; numerical robustness; power generation planning; true costing approach; unit commitment scheduling algorithm; Costing; Costs; Genetic algorithms; Genetic mutations; Lagrangian functions; Power system dynamics; Power systems; Processor scheduling; Robustness; Scheduling algorithm;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.536120

Filename

536120