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- W3001862077 abstract "The pollution performance of insulators installed in transmission and distribution lines plays a key role in maintaining the reliability, safety and cost-effectiveness of power systems. Among the different insulator monitoring techniques, leakage current stands out as one of the most meaningful pollution performance indicators as it gives a measure of how close the insulators string is to flashover. This paper presents a novel methodology for the prediction of the leakage current on insulator strings considering the environmental and weather information of the insulators location. It is based on the combination of a new developed Cumulative Pollution Index (CPI), which estimates the soluble pollution deposit on the insulator string, and a machine learning technique such as Random Forests algorithm. The method is valid for ceramic insulators, i.e., toughened glass, as well as RTV silicone-coated insulators with hydrophobic transfer properties. The research is supported by an extensive field monitoring program where three different insulator strings composed by non-coated, half-coated (bottom part) and full-silicone-coated glass insulators were monitored in a period covering twenty-two consecutive months. Finally, the performance of the proposed prediction model is evaluated using real data." @default.
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- W3001862077 date "2020-10-01" @default.
- W3001862077 modified "2023-09-27" @default.
- W3001862077 title "A Cumulative Pollution Index for the Estimation of the Leakage Current on Insulator Strings" @default.
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- W3001862077 doi "https://doi.org/10.1109/tpwrd.2020.2968556" @default.
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