A parallel genetic algorithm for generation expansion planning

Author

Fukuyama, Yoshikazu ; Chiang, Hsaio-Dong

Author_Institution

Fuji Electr. Corp. Res. & Dev. Ltd., Tokyo, Japan

Volume

11

Issue

2

fYear

1996

fDate

5/1/1996 12:00:00 AM

Firstpage

955

Lastpage

961

Abstract

This paper presents an application of parallel genetic algorithm to optimal long-range generation expansion planning. The problem is formulated as a combinatorial optimization problem that determines the number of newly introduced generation units of each technology during different time intervals. A new string representation method for the problem is presented. Binary and decimal coding for the string representation method are compared. The method is implemented on transputers, one of the practical multi-processors. The effectiveness of the proposed method is demonstrated on a typical generation expansion problem with four technologies, five intervals, and a various number of generation units. It is compared favorably with dynamic programming and conventional genetic algorithm. The results reveal the speed and effectiveness of the proposed method for solving this problem

Keywords

combinatorial mathematics; dynamic programming; electric power generation; multiprocessing systems; parallel algorithms; power system CAD; power system planning; transputers; CAD; binary coding; combinatorial optimization problem; decimal coding; generation units; long-range generation expansion planning; multi-processors; parallel genetic algorithm; power systems; time intervals; transputers; Concurrent computing; Costs; Dynamic programming; Economic forecasting; Electronics packaging; Environmental economics; Fuel economy; Genetic algorithms; Power generation economics; Stochastic processes;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.496180

Filename

496180