Systematic Framework for Integration of Weather Data into Prediction Models for the Electric Grid Outage and Asset Management Applications
Systematic Framework for Integration of Weather Data into Prediction Models for the Electric Grid Outage and Asset Management Applications
Files
Date
2018-01-03
Authors
Kezunovic, Mladen
Obradovic, Zoran
Djokic, Tatjana
Roychoudhury, Shoumik
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
Ending Page
Alternative Title
Abstract
This paper describes a Weather Impact Model (WIM) capable of serving a variety of predictive applications ranging from real-time operation and day-ahead operation planning, to asset and outage management. The proposed model is capable of combining various weather parameters into different weather impact features of interest to a specific application. This work focuses on the development of a universal weather impacts model based on the logistic regression embedded in a Geographic Information System (GIS). It is capable of merging massive data sets from historical outage and weather data, to real-time weather forecast and network monitoring measurements, into a feature known as weather hazard probability. The examples of the outage and asset management applications are used to illustrate the model capabilities.
Description
Keywords
Resilient Networks,
Weather predictions; outage management; asset management; data analytics
Citation
Extent
10 pages
Format
Geographic Location
Time Period
Related To
Proceedings of the 51st Hawaii International Conference on System Sciences
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Collections
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.