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1 Ergebnisse
1
Deep Learning based Security-Constrained Unit Commitment Co..:
, In:
2022 North American Power Symposium (NAPS)
,
Tuo, Mingjian
;
Li, Xingpeng
- p. 1-6 , 2022
Link:
https://doi.org/10.1109/NAPS56150.2022.10012162
RT T1
2022 North American Power Symposium (NAPS)
: T1
Deep Learning based Security-Constrained Unit Commitment Considering Locational Frequency Stability in Low-Inertia Power Systems
UL https://suche.suub.uni-bremen.de/peid=ieee-10012162&Exemplar=1&LAN=DE A1 Tuo, Mingjian A1 Li, Xingpeng YR 2022 SN 2833-003X K1 Deep learning K1 Training K1 Simulation K1 Power system stability K1 Predictive models K1 Mathematical models K1 Stability analysis K1 Frequency stability K1 Learning-embedded optimization K1 Low-inertia power systems K1 Renewable integration K1 Rate of change of frequency K1 Unit commitment SP 1 OP 6 LK http://dx.doi.org/https://doi.org/10.1109/NAPS56150.2022.10012162 DO https://doi.org/10.1109/NAPS56150.2022.10012162 SF ELIB - SuUB Bremen
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