Probabilistic Small-Signal Stability Analysis Of Power System Integrated With Large-Scale Wind Generation

Wind energy is one of the cheapest and cleanest sources of electrical energy. With the continuous increasing of wind power integrating in the system in recent years, the stochastic and fluctuating characters of wind power may threaten the security and stability of the power grid. Based on the current researches, large-scale wind power accessing to the power grid may produce a great impact on the power system small-signal stability. However, the traditional deterministic small-signal analysis method can’t be applied to the complex modern power system contains a lot of uncertain factors. Therefore, considering the correlation between the wind farms and the probabilistic wind power production, this dissertation studied and explored the probabilistic analysis of small-signal stability of power systems as affected by large-scale wind power, based on the TPNT-PEM analysis method.Firstly, in order to investigate the impacts of large-scale wind power generation connected to an existing power grid on the small-signal analysis of power system, the dynamic model of DFIG wind turbine and the aggregated model of wind farm have been constructed. The dynamic model of DFIG wind turbine consists of aerodynamic system model, electrical system model and the corresponding control system model. Considering system scenario, the analysis precision and computational efficiency, the aggregated wind farm model with an equivalent wind turbine was established for analyzing small-signal stability. Furthermore, the sixteen-machine five-area test system with large-scale wind generation was established to investigate the impact of wind power integration on power system dynamic stability.Secondly, based on the test system, the deterministic small-signal stability analysis method was used to investigate the impact and mechanism of large-scale wind power integration. Different factors were considered, including system power flow, system load capacity, wind farm locations and wind power penetration levels. The results demonstrate the mechanism and impact of large-scale wind power integration, which provides a significant reference for the safe and stable operation of actual power system.Then, the TPNT-PEM probabilistic small-signal stability analysis method was proposed, considering the probabilistic production of wind farm and the correlation between wind farms. The third-order polynomial normal transformation was used to dispose the correlation, meanwhile the system state matrix eigenvalues were estimated by the 2m+1 points estimate method. C-type Gram-Charlier series was introduced into the proposed algorithm to avoid getting the negative value of probability density function.Lastly, in order to assess the risk of power system small-signal unstability, the concept of severity function and risk assessment index of probabilistic small-signal stability was introduced. The impact of wind power uncertainty is investigated for different wind power penetration levels and wind farm correlation degrees.