| Issue |
E3S Web Conf.
Volume 411, 2023
VI International Conference on Actual Problems of the Energy Complex and Environmental Protection (APEC-VI-2023)
|
|
|---|---|---|
| Article Number | 01001 | |
| Number of page(s) | 6 | |
| Section | Issues of the Energy Complex | |
| DOI | https://doi.org/10.1051/e3sconf/202341101001 | |
| Published online | 10 August 2023 | |
Identification of parameters of power transformer models using artificial intelligence methods
1 Financial University under the Government of the Russian Federation, Moscow, Russia
2 Vologda State University, Vologda, Russia
* Corresponding author: alyunov@mail.ru
A large number of tasks for analyzing the state of power transformers are solved on the basis of mathematical models, the validity of which is undeniable. The disadvantage of standard methods for diagnosing current-carrying parts of transformers is the requirement to remove voltage. The applied diagnostic methods without stress relief require improvement in terms of increasing accuracy, speed and ensuring predictive response. The paper presents methods for identifying the parameters of mathematical models of power transformers using artificial neural networks.
© The Authors, published by EDP Sciences, 2023
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