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eess.SY2022
Machine Learning Assisted Inertia Estimation using Ambient Measurements
Mingjian Tuo, Xingpeng Li
With the increasing penetration of converter-based renewable resources, different types of dynamics have been introduced to the power system. Due to the complexity and high order o…
eess.SY2022
Selectively Linearized Neural Network based RoCoF-Constrained Unit Commitment in Low-Inertia Power Systems
Mingjian Tuo, Xingpeng Li
Conventional synchronous generators are gradually being replaced by inverter-based resources, such transition introduces more complicated operation conditions. And the reduction in…
eess.SY2022
Deep Learning based Security-Constrained Unit Commitment Considering Locational Frequency Stability in Low-Inertia Power Systems
Mingjian Tuo, Xingpeng Li
With the goal of electricity system decarbonization, conventional synchronous generators are gradually replaced by converter-interfaced renewable generations. Such transition is ca…