Probabilistic Small Signal Stability Analysis Of Wind Integrated Power Systems Using PCM

With the continuous exploitation and increasing penetration of wind power,the wind’s randomicity and fluctuation have brought great uncertainties, highlighting the issue of secure and stable operation of the power system. Therefore, it is worthy paying attention to the impact of large-scale wind power integration on small signal stability of the power system. Traditional deterministic eigenvalue analysis can hardly reflect security operation level of the power system practically due to the inability to consider uncertainties of wind power. Based on it, this paper proposes an effective probabilistic collocation methods(PCM)-based method for probabilistic small signal stability analysis, applicable to the study of the impact of wind power integration on small signal stability of the power system.Firstly, the paper introduces in detail four common probabilistic analysis methods for uncertainty assessment of the power system, namely: Monte Carlo(MC) methods, point estimation methods(PEM), cumulant methods(CM), and probabilistic collocation methods. The accuracy and computational efficiency of these methods are compared through probabilistic load flow calculations, and the advantages of PCM in uncertainty assessment of power system are summarized over the other methods.Secondly, the application of PCM in probabilistic small signal analysis of the power system is investigated. In light of the mechanism and basic concepts of eigenvalue analysis, the PCM model of the input variable is established, and the flow of PCM-based probabilistic small signal characteristic analysis of the power system is presented in detail. The simulation results show that probabilistic characteristics of frequency and damping ratio of the dominant oscillation mode by means of PCM keep consistent with that of MC. In other words, PCM can effectively evaluate the probabilistic small signal characteristics of the power system with good accuracy and far higher computational efficiency than MC.Finally, a PCM-based method for probabilistic small signal stability analysis of wind integrated power systems is proposed in this paper. The PCM probability model of wind power is established in consideration of the discontinuity of its characteristics. Then the indexes are put forward for probabilistic small signal stability, and the detailed procedure of the PCM-based probabilistic small signal stability analysis of integrated power system is given. Case studies are carried out on 10-machine New England test system with wind farms. Simulation analysis indicates that the established PCM probability model of wind power output can accurately reflect the operating characteristics of wind power. In addition, the small signal stability of the entire wind power system shows a decreasing trend with the increasing share of the wind power.