Study On Probabilistic Small-Signal Stability Of Power System Considering Large-Scale Wind Power Connection

Various types of stochastic sources exist in power system, which makes the system filled with uncertainty. The traditional methods are not subjected to the problems associated with the uncertain. Because, generally, it cannot evaluate the practical situation in power system. As a result, based on the probabilistic theory, the probabilistic method is proposed, which is effective in the field of study of probabilistic plow flow and stability. With the techonolgy of wind power developing, the capacity of a single wind turbine and the penetration rate of wind power in power system have been increasingly booming, which brings about the wind power as a new stochastic source to power system. As for the power system connecting with large-scale wind farms, the wind power is the input random variable whose mobility scale is great. The conventional probabilistic analytical method, such as the point estimate method and the cumulants method, are not suitable because of its own flaws. Consequently, a new probabilistic method that can be subjected to the study of small-signal probabilistic stability of the power system connecting with large-scale wind farms is desiderated.In allusion to the power system containing large-scale DFIG wind farms, the dynamic model of DFIG applying to the study of small-signal stability is set up in this thesis. Then the model of large-scale DFIG wind farm, based on the weighting aggregation method, is obtaioned. As last, associated with dynamic models of other components in power system, the dynamic model of the power system connecting with large-scale wind farms that is appropriate to probabilistic small-signal stability study is proposed.To describe the randomness of wind power, the probabilistic model of wind speed based on the linear least square method is obtained. In account of the history data and the transfer function of wind power, the sample of wind power is also acquired. Then the Levenberg-Marquardt method is adopted to fit the probabilistic density function of wind power based on the wind power sample obtained above. By comparing with the empirical formula of probabilistic density function of wind power, the most accurate solution is accquired based on the precise gauges. And the stochastic model of wind power is set up, which lay a foundation for the calculation of cumulants of wind power.In order to analyze the small-signal stability of the power system containing large-scale DFIG wind farms, the method of multi-linearization associated with the cumulants is proposed. The flunction of wind power will lead to the drifting of equilibrium point. In this essay, the stochastic source is introduced into the initial status of the established state equation. And the cumulants of wind power is acquired based on the stochasitc model of wind power. Then the multi-linearization method is imported, which sets up the linear associaton between wind power and eigenvalues of electromechnical oscillation modes in a divisive approach. Finally, the cumulants of eigenvalues of electromechnical oscillation modes is obtained, based on which can calculate the probabilistic density function.At last, the accuarcy of the new method is vertified associated with the standard example of IEEE 4 machines 11 nodes system. And based on the new method, the small-signal stability of the power system containing large-scale DFIG wind farms is studied.