Real-Time Prediction of the Duration of Distribution System Outages
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Abstract (arXiv)
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.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Apr 2018.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 1; 2025: 3.
6 papers.
- 2022Massively Digitized Power Grid: Opportunities and Challenges of Use-inspired AIcited by 6
- 2024Deep Learning-Based Weather-Related Power Outage Prediction with Socio-Economic and Power Infrastructure Datacited by 2
- 2025A Hybrid PCA-PR-Seq2Seq-Adam-LSTM Framework for Time-Series Power Outage Predictioncited by 1
- 2025Graph Attention Network for Predicting Duration of Large-Scale Power Outages Induced by Natural Disasterscited by 1
- 2022End-to-End Topology-Aware Machine Learning for Power System Reliability Assessmentcited by 0
- 2025Predictive Modeling of Power Outages during Extreme Events: Integrating Weather and Socio-Economic Factorscited by 0
- 2025Predictive Modeling of Power Outages during Extreme Events: Integrating Weather and Socio-Economic Factors27 Dec 2025
- 2025Graph Attention Network for Predicting Duration of Large-Scale Power Outages Induced by Natural Disasters14 Nov 2025
- 2025A Hybrid PCA-PR-Seq2Seq-Adam-LSTM Framework for Time-Series Power Outage Prediction20 Sep 2025
- 2024Deep Learning-Based Weather-Related Power Outage Prediction with Socio-Economic and Power Infrastructure Data3 Apr 2024
- 2022End-to-End Topology-Aware Machine Learning for Power System Reliability Assessment30 May 2022
- 2022Massively Digitized Power Grid: Opportunities and Challenges of Use-inspired AI10 May 2022