Thermal prognosis of dry-type transformer: Simulation study on load and ambient temperature impacts

Bagheri, Mehdi; Subramaniam, Aravinth; Bhandari, Saurabh; Chandar, Subash; Nadarajan, Sivakumar; Gupta, Amit Kumar; Panda, Sanjib Kumar

doi:10.1109/iecon.2015.7392256

Cited by 6 publications

(1 citation statement)

References 8 publications

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“…However, these thermal models have one thing in common, which is the study of heat propagation. Radiation, convection, and conduction are considered the fundamental pillars in the study of heat transfer in the transformer [3], [17]; hence, a complex theoretical set of equations is required to predict temperature [3].…”

Section: Heat Transfermentioning

confidence: 99%

Hot-Spot Temperature Forecasting of the Instrument Transformer Using an Artificial Neural Network

Juarez-Balderas¹,

Medina-Marín

Olivares-Galván

et al. 2020

IEEE Access

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Cast resin medium voltage instrument transformer are highly used because of several benefits over other type of transformers. Nevertheless, the high operating temperatures affects their performance and durability. It is important to forecast the hot spots in the transformer. The aim of this study is to develop a model based on Artificial Neural Networks (ANN) theory to be able to forecast the temperature in seven points, taking into account twenty-six input data of transformer design features. 792 simulations were carried out in COMSOL Multiphysics®to emulate the heat transfer in the transformer. The data obtained were used to train 1110 ANN with different number of neurons and hidden layers. The ANN with the best performance (R = 1, MSE=0.003455) has three hidden layers with 10, 9 and 9 neurons respectively. The ANN predictions were validated with finite element simulations and laboratory thermal tests which present similar patterns. With this accuracy in the prediction of hot-spot temperature, this ANN can be used to optimize the design of instrument transformers. INDEX TERMS Artificial neural networks, resin-cast instrument transformer, epoxy resins, finite element analysis, hot-spot temperature

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Section: Heat Transfermentioning

confidence: 99%