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This document presents a novel method for estimating the economic replacement time of transformers using a combination of Monte Carlo algorithms and artificial neural networks (ANN). The approach incorporates economic analysis alongside technical considerations, utilizing Pareto distribution to account for transformer health history and uncertainties in performance. Simulation results indicate high accuracy in predicting the optimal replacement time, thereby aiding in effective asset management of power tra

Author

kurniawan.fanni10

Language

EN