To address the coordinated optimization problem of transient stability and economy caused by wind power integration into power systems
a transient stability constrained optimal power flow (TSCOPF) model considering the dual uncertainties of wind power is proposed. Firstly
a bi-level Monte Carlo sampling method is employed to model the uncertainties arising from the distribution parameters of wind power and random fluctuations in wind speed
achieving a unified characterization of the dual uncertainties in wind power. Subsequently
a stacked ensemble Transformer (SET) model is utilized to establish the relationship between the input features of the power system and a constructed transient stability indices. Finally
an improved dung beetle optimizer (IDBO) is utilized to solve the TSCOPF model. Case study results demonstrate that the proposed method can effectively mitigate uncertainty risks and enhance the transient stability of the system.
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