Analysis And Research On Stability Of Power System Integrated With Wind Power Generation

Energy is the basic dynamic of economic and social development, and the limitations of conventional energy sources and distribution inhomogeneity make it cannot meet the needs of economic sustainable development. The development of renewable energy has become a global issue. Wind energy resources which are rich in our country has become the most important renewable energy after the hydro wind power. Large-scale wind power integration bring new challenges to power system scheduling and stable operation. It is essential for scheduling staffs to consider about how to make full use of wind energy, meantime ensuring safety and reliable power supply. Scheduling staffs need computer-aided tools such as probabilistic load flow to analyze and compute power system.Compared with the traditional energy sources, the biggest feature of wind power is uncertainty. It is a form of intermittent and random energy. At present, most program is based on certainty principle, but it is difficult to deal with uncertainty caused by large-scale wind power integration. The wind speed between different wind farm has strong correlation because of the geographical position close in the same wind, we can’t simply use one equivalent wind turbine to model the whole wind farm any more.Fist, this paper used the polynomial normal transformation method to deal with non-normal random variable correlation related, and putted forward a solution to solve probabilistic load flow based on Kriging method. In addition, to analyze the transient stability of power system integrated with wind farm groups, this paper applied Digital Nets method to compute system’s transient stability. Digital Nets method which has equidistributed sample values is applied to improve the sample values coverage of random variables input spaces. Compared with the traditional approaches which need more number of calculation times,long simulation time and need of memory space,the methods of this paper can rapidly estimate the probability distribution of the output random variables. Results obtained are used to compare with those by Monte Carlo-based accurate solution.The results prove the validity and veracity of the model in wind farm power modeling as the actual turbines output on the platform of PSD-BPA and PSAT.