Location
Hilton Waikoloa Village, Hawaii
Event Website
http://hicss.hawaii.edu/
Start Date
1-3-2018
End Date
1-6-2018
Description
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.
Systematic Framework for Integration of Weather Data into Prediction Models for the Electric Grid Outage and Asset Management Applications
Hilton Waikoloa Village, Hawaii
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.
https://aisel.aisnet.org/hicss-51/es/resillient_networks/4