Probabilistic transient stability assessment of power system considering wind power uncertainties and correlations

This paper proposes a simple yet effective method for power system probabilistic transient stability assessment considering the wind farm uncertainties and correlations. Specifically, the inverse Nataf transformation based three-point estimation method and the Cornish-Fisher expansion have been integrated together to deal with the uncertainties and the correlations among different wind farms. Then, by resorting to the extended dynamic security region approach, the transient stability criterion is derived as a linear combination of nodal injection vector under a given fault condition. New indices for the identification of critical lines have also been developed. Extensive simulation results carried out on four different systems, including the practical GZ power system in China show that the computational efficiency of the proposed method is much higher than the Monte Carlo based method and other methods almost without the loss of accuracy. The effectiveness of the proposed method under different penetrations of wind power with different degree of correlations is also validated. It is shown that correlation among wind farms has a larger impact on the transient stability results with a higher penetration level of renewable energy.