基于CFD流场预计算的短期风速预测方法

Short-term Wind Speed Forecasting Based on CFD Pre-calculated Flow Fields

风电功率预测有利于减轻风力发电对电网的冲击、提高电网运行的安全性和经济性,准确预测风速是风电功率预测的关键。提出一种基于计算流体力学(computational fluiddynamics,CFD)流场预计算(CFD pre-calculated flow fields,CPFF)的短期风速预测方法:首先,对可能出现的风电场来流条件离散化,并利用CFD模型对不同来流条件下的流场进行预计算;其次,提取各来流条件下流场特定位置的风速和风向分布,组成流场特性数据库;最后,以中尺度数值天气预报数据为输入参数,利用数据库插值预测风电机组轮毂高度的风速和风向。以中国北方某风电场为例,采用文中方法进行为期一年的提前24小时风速预测。通过与风机实测风速数据对比,结果表明:各台机组轮毂高度的预测风速年平均绝对误差小于2 m/s,年均方根误差小于2.5m/s,而且误差越小的预测风速出现的概率越大。所提预测方法不但预测精度高、稳定性好,而且由于复杂的流场计算在预测前完成,预测过程简单、耗时少,工程实用性强。

Wind power prediction is of great significance for the safe and economic operation when large-scale wind power is connected to the electricity grid.Forecasting the wind speed accurately is essential for wind power prediction.A novel approach for short-term wind speed forecasting was put forward which is based on the computational fluid dynamics（CFD） pre-calculated flow fields（CPFF）.Firstly,it discretizes the inflow conditions,and pre-simulates the wind fields affected by wind farm’s terrain and roughness using CFD model on various inflow conditions.Then the flow field characteristics are extracted from all the simulated flow fields to compose a database.Finally,by coupling the mesoscale NWP input data with the reference mast,the site-specific wind at the hub height of wind turbines can be predicted using the database.This approach was verified taking a wind farm located in north China for example and the results were compared to the measured wind speed.The annual RMSE of wind velocity at every turbine’s hub is less than 2.5m/s and the MAE is less than 2.0m/s,besides,the larger the absolute error of predicted wind velocity,the smaller its appearing probability.It can be concluded that the forecasting approach is not only of high accuracy and stability,but also short time demanding and especially practical for the engineering projects because the complicated CFD calculations were done before forecasting.