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ANN ensemble and output encoding scheme for improved transformer tap-changer operation

conference contribution
posted on 06.12.2017, 00:00 authored by Md Fakhrul IslamMd Fakhrul Islam, Joarder KamruzzamanJoarder Kamruzzaman
Voltage control of power transmission and distribution system using artificial neural network (ANN) based tap-changer control has a number of potential advantages when the parallel transformers are connected across the power network. Previous development of ANN based tap-changer control were made using modified cascade correlation learning algorithm incorporating the Bayesian framework and produced above 99% correct tap-changer operation in average. This paper investigates and exploits a suitable output coding and ensemble principle in the design of ANN based tap-changer control to further enhance its performance producing more than 99.95% correct tap-changer operation. Ultimately, the ensemble design makes the ANN based control more reliable. Performances of ANN ensembles for tap-changer control are analyzed and results are presented.

History

Parent Title

2006 IEEE PES Power Systems Conference and Exposition Proceedings, Oct. 29 2006-Nov. 1 2006, Atlanta, GA.

Start Page

1063

End Page

1068

Number of Pages

6

Start Date

01/01/2006

ISBN-10

1424401771

Location

Atlanta, GA

Publisher

IEEE

Place of Publication

Piscataway, NJ

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Monash University; Power Systems Conference & Exposition;

Era Eligible

Yes

Name of Conference

IEEE Power Engineering Society. Power Systems Conference & Exposition.