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- W3208807229 abstract "Nowadays, a power system failure can drastically affect the reliability and normal operation of power distribution grids. The preparation for these failure events is currently approached with post-event analysis to identify the area of the system that requires the most resources in order to prevent future failures. Nevertheless, the forecasting of such events can be useful to anticipate the failure and possibly avoid it. In this work, we employ several machine learning approaches to analyze historical failure data and predict power grid outages based on operational and meteorological data. The approach is tested with real failure data of a power distribution network in the South of Italy, demonstrating advantageous results also to determine areas requiring particular attention." @default.
- W3208807229 created "2021-11-08" @default.
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- W3208807229 date "2021-09-07" @default.
- W3208807229 modified "2023-09-23" @default.
- W3208807229 title "Effects of Heatwaves on the Failure of Power Distribution Grids: a Fault Prediction System Based on Machine Learning" @default.
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- W3208807229 doi "https://doi.org/10.1109/eeeic/icpseurope51590.2021.9584751" @default.
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