A Machine Learning Framework for Bridging the Gap Between the Steady-State Scheduling and Dynamic Security Operation for Future Power Grids

Tan, Jin (ORCID:0000000205997730)

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DOE OSTI · 1822172

A Machine Learning Framework for Bridging the Gap Between the Steady-State Scheduling and Dynamic Security Operation for Future Power Grids

Tan, Jin (ORCID:0000000205997730)

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Abstract

This presentation was part of an invited talk for a panel session presented at the 2021 IEEE Power & Energy Society General Meeting, held 26-29 July 2021.

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BibTeX RIS

Tan, Jin (ORCID:0000000205997730). 2021-09-20. A Machine Learning Framework for Bridging the Gap Between the Steady-State Scheduling and Dynamic Security Operation for Future Power Grids. https://www.osti.gov/biblio/1822172

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