Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/50234

Systematic Framework for Integration of Weather Data into Prediction Models for the Electric Grid Outage and Asset Management Applications

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Title:Systematic Framework for Integration of Weather Data into Prediction Models for the Electric Grid Outage and Asset Management Applications
Authors:Kezunovic, Mladen
Obradovic, Zoran
Djokic, Tatjana
Roychoudhury, Shoumik
Keywords:Resilient Networks
Weather predictions; outage management; asset management; data analytics
Date Issued:03 Jan 2018
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.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/50234
ISBN:978-0-9981331-1-9
DOI:10.24251/HICSS.2018.346
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Resilient Networks


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