A forecasting methodology based on second-generation wavelets and neural networks: application to power transformer oil temperature
Author:
Funder
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00202-023-02134-5.pdf
Reference59 articles.
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2. Kulkarni SV, Khaparde SA (2004) Transformer Engineering Design and Practice. Marcel Dekker Inc, New York
3. IEEE Guide for Loading Mineral-Oil-Immersed Transformers and Step-Voltage Regulators. IEEE Std C57.91-2011 (Revision of IEEE Std C57.91-1995), 1–123 (2012) https://doi.org/10.1109/IEEESTD.2012.6166928
4. Tylavsky DJ, He Q, McCulla GA, Hunt JR (2000) Sources of error in substation distribution transformer dynamic thermal modeling. IEEE Trans. Power Del. 15(1):178–185. https://doi.org/10.1109/61.847248
5. Hwang MD, Grady WM, Sanders HW (1988) Calculation of winding temperatures in distribution transformers subjected to harmonic currents. IEEE Trans. Power Del. 3(3):1074–1079
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