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仿真程度高且简洁实用的风模型,对于风力机系统的气动与结构设计、风场布置与发电功率预测等十分重要。实际风速时间序列普遍具有自相似性,传统的谐波叠加法生成风速不具有自相似特征。基于随机型Weierstrass-Mandelbrot函数,通过其功率谱与Kaimal脉动风速功率谱建立联系,生成具有自相似分形特性的风速时间序列。将该方法生成风速与谐波叠加法生成风速从功率谱、概率密度函数及均值、极值、标准差等统计参数方面进行比较。结果表明:相比于谐波叠加法,随机型W-M函数能有效仿真具有自相似分形特性的风速时间序列。
The high degree of simulation and simple and practical wind model are very important for the aerodynamic and structural design of wind turbine system, wind farm layout and power generation forecast. The actual wind speed time series generally has the self-similarity, and the traditional harmonic superposition method does not have the self-similar feature to generate wind speed. Based on the random Weierstrass-Mandelbrot function, the power spectrum is correlated with the power spectrum of Kaimal pulsating wind speed to generate the wind speed time series with self-similar fractal characteristics. The wind speed generated by this method and harmonic superposition method are compared in terms of power spectrum, probability density function and statistical parameters such as mean value, extreme value and standard deviation. The results show that compared with the harmonic superposition method, the random W-M function can effectively simulate the wind speed time series with self-similar fractal characteristics.