A machine learning framework for bridging the gap between the steady-state scheduling and dynamic security operation for future power grids / / Jin Tan
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| Autore: |
Tan Jin (Engineer)
|
| Titolo: |
A machine learning framework for bridging the gap between the steady-state scheduling and dynamic security operation for future power grids / / Jin Tan
|
| Pubblicazione: | [Golden, Colo.] : , : National Renewable Energy Laboratory, , 2021 |
| Descrizione fisica: | 1 online resource (23 pages) : color illustrations, color maps |
| Soggetto topico: | Machine learning |
| Electric power distribution - Security measures - United States | |
| Note generali: | Slideshow presentation. |
| "7/26/2021; presented at IEEE PES GM 2021." | |
| Titolo autorizzato: | A machine learning framework for bridging the gap between the steady-state scheduling and dynamic security operation for future power grids |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910717268403321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |