By Topic

Distribution system reliability worth analysis with the customer cost model based on RBF neural network

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)
Whei-Min Lin ; Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan ; Tung-Sheng Zhan ; Chin-Der Yang

Reliability worth analysis is an important tool for distribution systems planning and operations. The interruption cost model used in the analysis directly affects the accuracy of the reliability worth evaluation. In this paper, two interruption cost models including an average or aggregated model (AAM), and a probabilistic distribution model (PDM) are proposed by using the radial basis function (RBF) neural network with orthogonal least-squares (OLS) learning method. The residential and industrial interruption costs in AAM and PDM were integrated by the proposed neural network technique. A Monte-Carlo time sequential simulation technique was adopted for worth assessment. The technique is tested by evaluating the reliability worth of a Taipower system for the installation of disconnected switches, lateral fuses, transformers, and alternative supplies. The results show that the two cost models result in very different interruption costs, and PDM may be more realistic in modeling the system.

Published in:

Power Delivery, IEEE Transactions on  (Volume:18 ,  Issue: 3 )