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 :
بازگشت