A Novel Stochastic Cloud Model for Statistical Characterization of Wind Turbine Output

To overcome the problems of wind power forecast for the current deterministic wind power turbine output model cannot accurately describe the statistical characterization of wind turbine output, this article proposes a novel wind power stochastic cloud model. There are three steps to build this model. Firstly, it is necessary to analyze the power data and to filter out the disturbed data by utilizing the improved Bin method and data fitting. Secondly, it is available to obtain respectively two groups of the expectation, entropy and hyper entropy of the waist and upper data of stochastic cloud model by the known and unknown membership of backward cloud generators. Finally, the wind-speed data can be transformed into a stochastic cloud model, which is composed of X condition cloud generator and the positive cloud generator component. In short, the comparative data of the wind power cloud droplets and the measured data of wind power show that the line correlation coefficient of the wind power frequency of the proposed model reaches to 0.8868, which could simulate the statistical characterization of wind turbine output effectively.