大气模式物理过程参数化对风电场风速预报的影响

Impact of Physical Process Parameterization on Simulation of Wind Speed Forecasting

准确预报风电场风电功率对风电稳定发展至关重要,可有效减轻风电对电网的不利影响,提高风电场运行效益,其前提是准确预报风电场风速。以宁夏某风电场为例,基于中尺度大气模式WRF,采用不同物理过程参数化方案设置对提前72h的逐时风速进行预报,并将预报结果与实际风速资料对比,分析了WRF模式不同物理过程参数化方案设置对风速预报结果准确度的影响,并优化了物理过程参数化方案设置。结果表明,行星边界层参数化方案与辐射过程参数化方案设置对风速预报结果准确性影响较大,微物理过程参数化方案与积云对流参数化方案设置对风速预报结果准确性影响较小。

The accurate wind power forecasting is important for development of wind power industry and guarantees operation safety and stability of the wind farm, improving the benefit of wind farm. Wind power forecasting is the premise of wind speed forecasting. Taking a wind farm in Ningxia Province for an example, different physical process parameterization schemes are adopted to forecast the 72-hours wind speed based on middle scale WRF model. Compared with actual wind speed data, it analyzes the influence of physical process parameterizations in WRF model on simulation of wind speed forecasting and optimizes the physical process parameterizations scheme. The results show that the planet boundary layer parameterization schemes and radiation parameterization schemes have large impact on accuracy forecast wind speed, and the microphysics parameterization schemes and cumulus parameterization have little impact on accuracy forecast wind speed.