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Title:Optimization of transformer loading based on hot-spot temperature using a predictive health model
Authors:G. Bajracharya, T. Koltunowicz, R.R. Negenborn, D. Djairam, B. De Schutter, J.J. Smit

Conference:International Conference on Condition Monitoring and Diagnosis 2010 (CMD 2010)
Address:Tokyo, Japan
Date:September 2010

Abstract:In the future grid, power equipment will need to work with distributed generation, deregulation, and accelerated aging. To this end, a model-based framework for the optimization of usage of power equipment is proposed. The framework uses a predictive health model of the equipment in order to optimize the usage of the equipment. In particular, the predictive health model predicts the hot-spot temperature of the transformers in a network over a future time window based on the expected loading. The allowed loading limits of the transformers are based on the hot-spot temperature. Therefore, the optimal loading of the transformers is maintained by performing an optimal power flow (OPF) computation of the network that takes into account hot-spot temperature dynamics. The optimization determines values for the tap position of the transformers and the active and reactive power of generators in the network. Moreover, shedding of the loads in the network is considered when the aforementioned options are not sufficient to control the loading of the transformers. A case study using the IEEE 14-bus benchmark system is presented. The shedding of the loads is minimized by using this technique.

Reference:Optimization of transformer loading based on hot-spot temperature using a predictive health model. G. Bajracharya, T. Koltunowicz, R.R. Negenborn, D. Djairam, B. De Schutter, J.J. Smit. In Proceedings of the 2010 International Conference on Condition Monitoring and Diagnosis (CMD 2010), Tokyo, Japan, pp. 914-917, September 2010.

BibTeX:
@inproceedings{Negenborn:10f,
  author    = {G. Bajracharya, T. Koltunowicz, R.R. Negenborn, 
               D. Djairam, B. {De Schutter}, J.J. Smit},
  title     = {Optimization of transformer loading 
               based on hot-spot temperature using a 
               predictive health model},
  booktitle = {Proceedings of the 2010 International Conference 
               on Condition Monitoring and Diagnosis},
  pages =     {914--917},
  address   = {Tokyo, Japan},
  month     = {September},
  year      = {2010}}
Download:Corresponding technical report


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