By Topic

A Differential Evolution Based Method for Power System 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
$33 $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

4 Author(s)
Zhao Yang Dong ; The School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Brisbane, QLD 4072, Australia (e-mail: ; Miao Lu ; Zhe Lu ; Kit Po Wong

Power system planning is a complex multi-objective optimization problem. It aims at locating the minimum cost of additional transmission lines that must be installed to satisfy the forecasted load in a power system. A number of different methods for power system planning have been investigated over the past decades. In this paper, a differential evolution (DE) based approach is proposed as an optimization tool to solve the power system planning problem. A comparison between genetic algorithms, evolutionary strategy (ES), and five different DE schemes are carried out on two benchmark power systems. The results shown that, as a relatively new heuristic optimization method, DE is able to provide robust and efficient solution to power system planning problems.

Published in:

2006 IEEE International Conference on Evolutionary Computation

Date of Conference:

0-0 0