A dynamic thermal based reliability model of cast-resin dry-type transformers

Azizian, Davood; Bigdeli, Mehdi; Fotuhi-Firuzabad, M.

doi:10.1109/powercon.2010.5666453

Cited by 14 publications

(18 citation statements)

References 5 publications

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“…Different heuristic algorithms have been employed to estimate the parameters of these RC thermal models. As it has been shown in [15], the simplified models are accurate enough for the thermal modeling of the dry-type transformer. Additionally, some detailed RC thermal models have been presented in [16,17] for the thermal modeling of the cast-resin dry-type transformer.…”

Section: Introductionmentioning

confidence: 93%

“…In the transient condition, the transferred thermal energy to each unit appears as an increase in the total energy and the unit behaves as an integrated capacitor [16]. If only one unit is selected in the windings and if the heat transfer from horizontal surfaces is neglected (heat transfer is assumed to occur in the radial direction) [2], the thermal behaviour of the winding and the cooling air (on top of the enclosure [27]) can be explained as following [15]: …”

Section: Rc Thermal Modelmentioning

confidence: 99%

“…Different life-time and transient thermal models have been presented for oil-immersed transformers [9][10][11][12][13]. There are few researches on dynamic thermal modeling of the dry-type transformers [14][15][16][17]. References [14,15] introduce simplified RC models for the dynamic thermal modeling of the dry-type transformers.…”

Section: Introductionmentioning

confidence: 99%

“…There are few researches on dynamic thermal modeling of the dry-type transformers [14][15][16][17]. References [14,15] introduce simplified RC models for the dynamic thermal modeling of the dry-type transformers. Different heuristic algorithms have been employed to estimate the parameters of these RC thermal models.…”

Section: Introductionmentioning

confidence: 99%

“…Employing the measured temperatures, the ANN models have been trained and the predicted temperatures are validated against experimental results, the RC thermal models [15][16][17] and the classic IEC method [25]. Afterwards, using the trained ANN models, the life-time and reliability of the cast-resin transformer are studied.…”

Section: Introductionmentioning

confidence: 99%

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A new cast-resin transformer thermal model based on recurrent neural networks

Azizian

Bigdeli

2017

Archives of Electrical Engineering

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Thermal modeling in the transient condition is very important for cast-resin dry-type transformers. In the present research, two novel dynamic thermal models have been introduced for the cast-resin dry-type transformer. These models are based on two artificial neural networks: the Elman recurrent networks (ELRN) and the nonlinear autoregressive model process with exogenous input (NARX). Using the experimental data, the introduced neural network thermal models have been trained. By selecting a typical transformer, the trained thermal models are validated using additional experimental results and the traditional thermal models. It is shown that the introduced neural network based thermal models have a good performance in temperature prediction of the winding and the cooling air in the cast-resin dry-type transformer. The introduced thermal models are more accurate for the temperature analysis of this transformer and they will be trained easily. Finally, the trained and validated thermal models are employed to evaluate the life-time and the reliability of a typical cast-resin dry-type transformer.

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Section: Introductionmentioning

confidence: 93%