A Neural Fuzzy Approach to Modeling the Top Oil Temperature of Power Transformer

Full text for this resource is not available from the Research Repository.

Nguyen, Huy Huynh, Shi, Juan and Reznik, Leon (2002) A Neural Fuzzy Approach to Modeling the Top Oil Temperature of Power Transformer. In: MS'02 : Proceedings of the Fourth International Conference on Modelling and Simulation : 11-13 November, 2002, Melbourne, Australia. Zayegh, Aladin, ed. Victoria University, Melbourne, pp. 27-31.


This paper presents an application of a new system modeling algorithm using neural fuzzy technique. The model is intended to forecast power transformer temperature characteristics in order to predict its behaviour. The forecast accuracy is compared with the IEEE and Massachusetts Institute of Technology (MIT) models. The real data from an 8000kVA power tranformer have been used for training and testing the models. Results show that the intelligent neural fuzzy model has achieved a better prediction against the IEEE and MIT models.

Item type Book Section
URI https://vuir.vu.edu.au/id/eprint/25383
ISBN 1862726175
Subjects Historical > FOR Classification > 0906 Electrical and Electronic Engineering
Current > Division/Research > Other
Keywords fuzzy logic, neural networks, neural fuzzy modelling, power tranformers
Download/View statistics View download statistics for this item

Search Google Scholar

Repository staff login