By Topic

Skeleton network reconfiguration for system restoration in restructured power industry

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

3 Author(s)
Jafarian, H. ; Ferdowsi Univ. of Mashhad, Mashhad, Iran ; Mashhadi, M.R. ; Javidi, M.H.

Power system restoration is an important task for system operators. Due to the importance of the problem, the ways which will be used for solving it are significant as well. One of the best methods for restoring a power system is recognition and access to the network reconfiguration. If the main skeleton-network is recognized appropriately, other parts of the network can be restored at the shortest possible time. Restructuring in power industry add new complicated constraints to the problem of power system restoration. While this issue has been investigated by many researchers, little attention has been paid to this task in a market based environment. In most solving methods an index is defined to rank the network nodes. But none of the suggested indices have the comprehensiveness and also none of them considered the issues which have been dictated by the power market. This article represents a new combined index and market based method for ranking the network buses, which by applying it to different power systems; the best reconfigured network can be distinguished. Restoring other parts of the network from this skeleton network will lessen the restoration time. By using this index we can also decrease the cost of blackout and the cost of the power system restoration. This index in compare to similar indices has a better function and performs a better bus ranking for complicated power networks in market environment. Genetic algorithm is used to solve this problem. The suggested method is used to rank the buses of the IEEE 30-bus network. Results show that this method in compare with similar methods has a better performance.

Published in:

Electrical Engineering (ICEE), 2011 19th Iranian Conference on

Date of Conference:

17-19 May 2011