By Topic

A parallel genetic algorithm for generation expansion planning

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Fukuyama, Y. ; Fuji Electr. Corp. Res. & Dev. Ltd., Tokyo, Japan ; Hsaio-Dong Chiang

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

Published in:

Power Systems, IEEE Transactions on  (Volume:11 ,  Issue: 2 )