Optimization of condition-based asset management using a predictive health model


Reference:
G. Bajracharya, T. Koltunowicz, R.R. Negenborn, Z. Papp, D. Djairam, B. De Schutter, and J.J. Smit, "Optimization of condition-based asset management using a predictive health model," Proceedings of the 16th International Symposium on High Voltage Engineering, Cape Town, South Africa, pp. 1529-1534, Aug. 2009.

Abstract:
In this paper, a model predictive framework is used to optimize the operation and maintenance actions of power system equipment based on the predicted health sate of this equipment. In particular, this framework is used to predict the health state of transformers based on their usage. The health state of a transformer is hereby given by the hot-spot temperature of the paper insulation of the transformer and is predicted using the planned loading of the transformer. The actual loading of the transformer is subsequently optimized using these predictions.


Downloads:
 * Corresponding technical report: pdf file (148 KB)
      Note: More information on the pdf file format mentioned above can be found here.


Bibtex entry:

@inproceedings{BajKol:09-058,
        author={G. Bajracharya and T. Koltunowicz and R.R. Negenborn and Z. Papp and D. Djairam and B. {D}e Schutter and J.J. Smit},
        title={Optimization of condition-based asset management using a predictive health model},
        booktitle={Proceedings of the 16th International Symposium on High Voltage Engineering},
        address={Cape Town, South Africa},
        pages={1529--1534},
        month=aug,
        year={2009}
        }



Go to the publications overview page.


This page is maintained by Bart De Schutter. Last update: December 15, 2015.