Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 5:00 PM ET (12:00 - 21:00 UTC). We apologize for the inconvenience.
By Topic

A geno-fuzzy optimization of power system reliability

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)
Abdelaziz, A.R. ; Dept. of Electr. Eng., Alexandria Univ., Egypt ; Gouda, S.A.M.

The concept of reliability apportionment is general and has even been applied to the allocation of man-machine reliability. Typically, however, the process of optimally apportioning individual component reliability to meet some desired system reliability level subject, perhaps, to constraints on cost, volume, weight, etc., has always been imprecise and vague at best. In real problems, the resource constraints are no more sacred then the objective system reliability; they are frequently flexible. In view of the inherent vagueness of the reliability objective as well as constraints in a typical ill-structured reliability apportionment problem, this paper formulates the nonlinear optimization problem in the fuzzy-set theoretic perspective based on the using of genetic algorithm as a search technique. The technique is called geno-fuzzy optimization technique (GFOT). To illustrate the philosophy, a simple reliability apportionment example with a budgetary constraint for a 3-component series/parallel structure is analyzed. Then the concept is generalized into a more realistic problem with multiple components and constraints.

Published in:

Electrotechnical Conference, 2000. MELECON 2000. 10th Mediterranean  (Volume:3 )

Date of Conference:

29-31 May 2000