考虑动态风速变异因子的风电功率预测

Prediction of Wind Power Considering Dynamic Wind Speed Variation Coefficient

山地风电场(MWFs)的风能资源丰富,但受复杂地形、地表粗糙度、近地大气稳定性等因素影响,风速突变性更明显。针对山区风能特征建立了风电功率预测模型,相较于平原地区,山区风能具有不同的波动性和间接性等特点;提出一种计及多分辨率下的动态风速变异因子预测方法,同时改进模糊聚类中的聚类组合指标,将气象条件在空间连续性上实现更精准的分类,以提高风电场功率出力预测的精度。为验证该模型的有效性,与常用K-means和时间序列方法进行对比,并对加入动态风速变异因子前后的预测效果进行对比,结果表明所提方法对风电场出力预测具有较高实用意义。

Mountainous wind farm(MWFs)are rich in wind energy resources,but the abrupt change of wind speed is more obvious due to the influence of complex terrain,surface roughness,near surface atmospheric stability and other factors.In this paper,the wind power prediction model is established according to the characteristics of wind energy in mountainous areas.Compared to the plain area,the wind energy in mountainous areas has different volatility and indirectness.A prediction method considering the dynamic wind speed variation factor under multi-resolution is proposed.At the same time,in order to improve the accuracy of wind farm power output prediction,the combination index of fuzzy clustering is improved to achieve more accurate classification of meteorological conditions in spatial continuity.In order to verify the effectiveness of the model,it is compared with the commonly used K-means and time series methods,and the prediction effects before and after adding dynamic wind speed variation factors are compared.The results show that the proposed method has high practical significance for wind farm output prediction.