Abstract
When substantial wind power generation is integrated into the power system, the low rotational inertia and uncertain power output of wind turbines pose a great challenge to the small-signal stability (SSS) of power system operation. In this paper, considering the dynamic model of a doubly fed induction generator (DFIG) and the uncertainty of wind power, we establish a bilayer robust optimization of the SSS constrained optimal power flow (SSSCOPF-RO) model for a power system with DFIGs. It uses Lyapunov's second theorem to describe the SSS constraint. By the semi-definite relaxation and McCormick envelope relaxation techniques, we transform the inner-layer optimization of the SSSCOPF-RO model into a semi-definite program (SDP) model to improve the convergence reliability and computational efficiency of solving the model. Based on the dual optimization theory, the inner-layer SDP model is converted into its dual SDP model, and the bilayer robust optimization model is transformed into a single-layer optimization model, which can be solved using the solver MOSEK in the software CVX. Finally, case studies were conducted on IEEE 9-, 39-, and 118-bus systems to validate the proposed method. The obtained optimal solution of the transformed single-layer optimization model could ensure the SSS of the system under the uncertain fluctuation of DFIGs’ active power output and effectively reduce the network loss cost, and the results indicate the effectiveness and robustness of the proposed model.
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