Optimization of Asset Management of Transformers Based on a Predictive
Health Model of Paper Degradation
Reference
G. Bajracharya,
T. Koltunowicz,
R.R. Negenborn,
D. Djairam,
B. De Schutter, and
J.J. Smit,
"Optimization of Asset Management of Transformers Based on a
Predictive Health Model of Paper Degradation," Proceedings of the 17th International Symposium on High
Voltage Engineering, Hannover, Germany, 6 pp., Aug. 2011. Paper
G-002.
Abstract
In this paper, a model-based predictive framework is proposed to
optimize the operation and maintenance actions for power system
equipment which operates in a changing environment of the future grid.
In this framework, a predictive health model is proposed that predicts
the health state of this equipment based on its operation and
maintenance actions. In particular, this framework is used to predict
the health state of transformers based on their usage and operating
environment. The hot-spot temperature of the transformer is predicted
from the expected loading of the transformer. Based on the hot-spot
temperature predictions, the allowed loading limits of the
transformers are determined. In the case of absence of the anticipated
loading of the transformer, a maximum allowable loading limit of the
transformer is estimated.
Downloads
- Corresponding technical report:
pdf
file
(265 KB)
Bibtex entry
@inproceedings{BajKol:11-046,
author={G. Bajracharya and T. Koltunowicz and R.R. Negenborn and D. Djairam and
B. {D}e Schutter and J.J. Smit},
title={Optimization of Asset Management of Transformers Based on a Predictive
Health Model of Paper Degradation},
booktitle={Proceedings of the 17th International Symposium on High Voltage
Engineering},
address={Hannover, Germany},
month=aug,
year={2011},
note={Paper G-002}
}
This page is maintained by Bart De Schutter.
Last update: February 21, 2026.