Improving emergency storm planning using machine learning

Improving emergency storm planning using machine learning

Extreme weather events pose significant challenges to power utilities as they require very rapid decision making regarding expected storm impact and necessary storm response efforts. In recent years National Grid has responded to a large number of events in its Massachusetts service territory includ...

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Bibliographic Details
Main Authors: Angalakudati, Mallikarjun (Author), Calzada, Jorge (Author), Gonynor, Jonathan (Author), Raad, Nicolas (Author), Schein, Jeremy (Author), Warren, Cheryl (Author), Williams, John (Author), Papush, Anna Michelle (Contributor), Monsch, Matthieu Frederic (Contributor), Farias, Vivek F. (Contributor), Perakis, Georgia (Contributor), Whipple, Sean David (Contributor)
Other Authors: Massachusetts Institute of Technology. Institute for Data, Systems, and Society (Contributor), Massachusetts Institute of Technology. Operations Research Center (Contributor), Sloan School of Management (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2018-06-11T19:12:22Z.
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