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

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.

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Abstract

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
ISBN: 1862726175
Uncontrolled Keywords: fuzzy logic, neural networks, neural fuzzy modelling, power tranformers
Subjects: FOR Classification > 0906 Electrical and Electronic Engineering
Faculty/School/Research Centre/Department > Other
Depositing User: Ms Julie Gardner
Date Deposited: 10 Jul 2014 05:43
Last Modified: 10 Jul 2014 06:02
URI: http://vuir.vu.edu.au/id/eprint/25383
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