Journal
IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 34, Issue 1, Pages 773-781Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2018.2860904
Keywords
Distribution system reliability; outage duration prediction; machine learning; text analysis; natural language processing
Categories
Funding
- NSF [1509880]
- Div Of Electrical, Commun & Cyber Sys
- Directorate For Engineering [1509880] Funding Source: National Science Foundation
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This paper addresses the problem of predicting duration of unplanned power outages, using historical outage records to train a series of neural network predictors. The initial duration prediction is made based on environmental factors, and it is updated based on incoming field reports using natural language processing to automatically analyze the text. Experiments using 15 years of outage records show good initial results and improved performance leveraging text. Case studies show that the language processing identifies phrases that point to outage causes and repair steps.
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