Abstract
Conference Title: 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Conference Start Date: 2018, June 24 Conference End Date: 2018, June 28 Conference Location: Boise, ID, USA This paper presents a statistical analysis for power outages in the distribution network. 6-year outage data in the service territory of one U.S. utility is used in the analysis, which includes several storms and hurricanes. The first part of this paper summarizes the outage data with a focus on weather event-related outages; the second part proposes a machine learning-based technique to predict the repair and restoration time after outages, which provides useful information for utilities' repair work scheduling and crew dispatching. A Deep Neural Network (DNN) is trained using supervised learning with 5-year outage data. The 6th year data is used to validate the performance of the trained DNN model.