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

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dc.contributor.authorKezunovic, Mladen
dc.contributor.authorObradovic, Zoran
dc.contributor.authorDjokic, Tatjana
dc.contributor.authorRoychoudhury, Shoumik
dc.date.accessioned2017-12-28T01:05:57Z
dc.date.available2017-12-28T01:05:57Z
dc.date.issued2018-01-03
dc.description.abstractThis 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.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2018.346
dc.identifier.isbn978-0-9981331-1-9
dc.identifier.urihttp://hdl.handle.net/10125/50234
dc.language.isoeng
dc.relation.ispartofProceedings of the 51st Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectResilient Networks
dc.subjectWeather predictions; outage management; asset management; data analytics
dc.titleSystematic Framework for Integration of Weather Data into Prediction Models for the Electric Grid Outage and Asset Management Applications
dc.typeConference Paper
dc.type.dcmiText

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