This paper is aimed at exploring the characteristic fluctuation of wind power based on samples from a certain wind farm. First, the paper is to analyze fluctuations of wind power at different time scales. According to a sliding difference algorithm to build wind power fluctuations evaluation. Wind power fluctuation index for different time scales are used to fit probability distributions, indicating that the best form of distribution of wind power fluctuations is t location scale distribution. Secondly, considering the wind power has the characteristics of non-linear, non-stationary signal of the data, it fully meets the wavelet neural network analysis of the characteristics of the data. Therefore, select wavelet neural network training and testing so as to make predictions about the future of the total power of wind farm. It points out the differences between different regions covered by the index from the fluctuation characteristics of wind power, thus further understanding the fluctuation characteristics of wind power: Influenced by the time and space distribution and other factors, there is a big difference between the output power fluctuation characteristics of single wind generator and wind farm, which is because of the different wind machine in the field by the wind energy differences, and the wake effect of organic groups, making frequent fluctuations in power distribution; the fluctuation of wind is gentle, i.e. with increasing spatial distribution scale, so gentle effect occurs to wind power fluctuations. Finally, through the analysis of the fluctuation characteristics of power, power factor and analyses the influence of the characteristics of fluctuation, the paper draws a conclusion of the following improvement programs to overcome the adverse effects of wind power fluctuation of power grid operation: the rational allocation of energy storage devices, expanding the coverage area of a wind farm, or improving the design of the windmill, which will make wind farms adapt to different wind directions, thus eliminating the impact of fluctuations on the power grid from the wind farm power output by the energy storage device, and covering the area of large wind farms can adapt to different wind directions, and with power complementary, it has achieved the amount of stable power transmission into the grid.
Data-Driven Distributionally Robust Chance-Constrained Unit Commitment With Uncertain Wind Power
