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|a Tan, Jin
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|0 http://id.loc.gov/authorities/names/no2022031018.
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|a A machine learning framework for bridging the gap between the steady-state scheduling and dynamic security operation for future power grids /
|c Jin Tan.
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|a [Golden, Colo.] :
|b National Renewable Energy Laboratory,
|c 2021.
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|a "7/26/2021; presented at IEEE PES GM 2021."
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|a Description based on online resource; title from PDF title page (NREL, viewed February 15, 2021)
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|b DE-AC36-08GO28308.
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|a U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office
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|a Machine learning.
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|a Electric power distribution
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