DocumentCode
25157
Title
Forecasting of the Transformer Core Destruction Factor by means of Multivariate Methods for Data Analysis
Author
Diaz, G.A. ; Romero, A.A. ; Mombello, E. ; Furlan, N.
Author_Institution
Univ. Nac. de San Juan (UNSJ), San Juan, Argentina
Volume
11
Issue
1
fYear
2013
fDate
Feb. 2013
Firstpage
492
Lastpage
498
Abstract
In designing and building of transformers, the core destruction factor is the superposition of all effects that cause a difference between the value of the core losses calculated during the design stage of the unit and the measured value after built. In this paper, two methods for forecasting the core destruction factor are proposed. One based on Mahalanobis distance and the other one based on cluster analysis. A comparison of the results obtained by conventional calculation procedure with respect to those obtained through the proposed methodologies is developed. Finally, the expected cost savings by applying the methods proposed in this article are estimated.
Keywords
data analysis; pattern clustering; transformer cores; Mahalanobis distance; cluster analysis; core losses; cost savings; data analysis; multivariate methods; transformer core destruction factor forecasting; Covariance matrices; Forecasting; Media; Reactive power; Robustness; Silicon compounds; Transformer cores; Mahalanobis distance; clustering; forecasting; transformer losses;
fLanguage
English
Journal_Title
Latin America Transactions, IEEE (Revista IEEE America Latina)
Publisher
ieee
ISSN
1548-0992
Type
jour
DOI
10.1109/TLA.2013.6502851
Filename
6502851
Link To Document