Cart (Loading....) | Create Account
Close category search window
 

A genetic based fuzzy approach to optimisation of electrical distribution networks

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 $31
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)
Strbac, G. ; Univ. of Manchester Inst. of Sci. & Technol., UK ; Djapic, P.

Electrical distribution networks are built as interconnected meshed networks, while in the operation they are arranged into radial, tree structures. The network configuration problem is to find a radial operating structure that optimises the network performance while satisfying operating constraints. In fact, this problem call be viewed as the problem of determining an `optimal' tree of the given graph. The problem is usually formulated as a constrained multi-objective combinatorial problem that belongs to the class of very large non-linear mixed-integer problems. In this paper a fuzzy co-ordination technique is used to identify overall degree of satisfaction, while GA is employed to maximise it. The major difficulty in the application of GA to this problem is that crossovers normally generate infeasible solutions, as random combination of parts of different trees of the same graph do not create a new three of that graph. The constraints are enforced by adjusting the new string to the `nearest' three which is, in terms of GA, adequate with performing `mutation' at each crossover. The results obtained by the proposed algorithm are compared with the previously developed `greedy' algorithms on a slightly changed real distribution system, showing that GA has a potential to address some other planning and operation problems in electrical distribution systems

Published in:

Genetic Algorithms in Engineering Systems: Innovations and Applications, 1995. GALESIA. First International Conference on (Conf. Publ. No. 414)

Date of Conference:

12-14 Sep 1995

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.