Real-Time Prediction of the Duration of Distribution System Outages

TL;DR

This paper presents a neural network-based approach for real-time prediction of power outage durations, utilizing environmental data and natural language processing of field reports to improve accuracy and identify outage causes.

Contribution

It introduces a novel combination of neural networks and NLP techniques for dynamic outage duration prediction using extensive historical data.

Findings

Good initial prediction accuracy

Improved performance with text analysis

NLP identifies outage causes and repair steps

Abstract

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.