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- W2963149404 abstract "Transformer life assessment and failure diagnostics have always been important problems for electric utility companies/Ambient temperature and load profile are the main factors which affect aging of the transforiner insulation, and consequently, the transformer lifetime. The IEEE Std. C57.91-1995 provides a model for calculating the transformer loss of life based on ambient temperature and transformer's loading. In this paper, this standard is used to develop a data-driven static model for hourly estimation of the transformer loss of life. Among various machine learning methods for developing this static model, the Adaptive Network-Based Fuzzy Inference System (ANFIS) is selected. Numerical simulations demonstrate the effectiveness and the accuracy of the proposed ANFIS method compared with other relevant machine learning based methods to solve this problem." @default.
- W2963149404 created "2019-07-30" @default.
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- W2963149404 date "2017-07-01" @default.
- W2963149404 modified "2023-10-14" @default.
- W2963149404 title "Machine learning applications in estimating transformer loss of life" @default.
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- W2963149404 doi "https://doi.org/10.1109/pesgm.2017.8274564" @default.
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