摘要
风速时间序列标度分析可为风能预测等提供决策支持,进而提高风能利用程度。结合工程实例,尝试了将在全局拟合、非线性处理和求解精度等方面表现较优的自适应分形分析方法引入至风速时间序列的标度研究。通过与目前常用的去趋势波动分析方法对比显示两种方法的局部标度指数和全局标度指数均十分接近,验证了在风速时间序列标度研究中使用自适应分形分析方法的可行性。
The scaling analysis of the wind speed time-series could provide decisional supports to the wind power predic- tion and improve its utilization rate. In this study, the adaptive fractal analysis method is adopted in the scaling analysis of the wind speed time-series, which is of better performance in the global fitting, nonlinear processing and accuracy. The results of practical engineering examples show that the local and global scaling exponents obtained from the adaptive fractal analysis method and the commonly used detrended fluctuation analysis method are very close, which proves the feasibility of the adaptive fractal analysis method in the scaling analysis of the wind speed time-series.
出处
《水电与新能源》
2017年第11期1-6,共6页
Hydropower and New Energy
关键词
风速时间序列
标度研究
自适应分形分析
局部标度指数
全局标度指数
wind speed time-series
scaling analysis
adaptive fractal analysis
local scaling exponent
global scalingexponent
