By Topic

A Bayesian network approach to power system asset management for transformer dissolved gas analysis

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)
Tang, W.H. ; Dept. of Electr. Eng. & Electron., Univ. of Liverpool, Liverpool ; Lu, Z. ; Wu, Q.H.

This paper presents a Bayesian network approach to dissolved gas analysis (DGA) problems for power transformers, which is easy to construct and able to interpret with formal probabilistic semantics. The effectiveness of the traditional IEEE/IEC coding scheme is validated using the proposed approach, which is also able to handle the missing codes in the traditional coding scheme. Firstly, the essential concepts of Bayesian networks are introduced, which are graphical representations of uncertain knowledge. The methodology of combining knowledge in the DGA domain with statistical data used to learn new knowledge is then described. A specific Bayesian network is designed to diagnose transformer faults based upon the IEEE/IEC DGA ratio method. An applicable solution to a transformer DGA problem, using the Bayesian network approach, is illustrated highlighting the potential of Bayesian networks. It can be seen from the results developed that the proposed approach is capable of tackling the DGA problem for power transformers as a supportive tool along with the IEEE/IEC DGA coding scheme.

Published in:

Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference on

Date of Conference:

6-9 April 2008