采用横纵向误差平移插值修正的风电预测精度改善方法

发布时间：2018-03-16 16:40

本文选题：风电功率预测　切入点：横向误差　出处：《电网技术》2015年10期 　论文类型：期刊论文

【摘要】：目前风电预测功率精度偏低,评估指标常用纵向误差,很少针对横向误差(延迟或超前时间)进行统计。提出了基于横、纵向误差平移修正的风电预测精度改善方法,给出用于风电功率预测的不变趋势功率持续时间的概念,并将风电场日前功率预测曲线和实际功率曲线划分为不变趋势功率增加段、降低段和保持段3种模式。建立了各不变趋势持续时间的计算模型,采用概率统计法获得预测时间值与实际时间值之间的偏差值及滞后或超前方向,利用平移法和插值法联合横纵向误差修正日前功率预测误差。应用上述方法对新疆某地区风电功率预测曲线进行仿真计算,结果如下:该地区风电功率预测横向误差为3.78 h,方向为超前,纵向绝对误差值为40.05 MW;采用平移插值修正后,横向误差值为2.56 h,降低了32.34%,纵向误差值为32.58 MW,降低了18.65%。从而表明该方法可以有效提高风电短期预测功率精度。
[Abstract]:At present, the accuracy of wind power prediction is on the low side, the longitudinal error is commonly used in the evaluation index, and the lateral error (delay or lead time) is seldom counted. A method to improve the accuracy of wind power prediction based on the translation correction of horizontal and longitudinal errors is proposed. The concept of constant trend power duration for wind power prediction is given, and the power prediction curve and actual power curve before wind farm are divided into constant trend power increase section. The models of the duration of each invariant trend are established, and the deviation value between the predicted time value and the actual time value and the direction of lag or advance are obtained by using the probability statistics method. By using the translation method and interpolation method combined with transverse and longitudinal error to correct the pre-day power prediction error, the wind power prediction curve in a certain area of Xinjiang is simulated and calculated by using the above method. The results are as follows: the lateral error of wind power prediction in this area is 3.78 h, the direction is ahead, and the absolute longitudinal error is 40.05 MW. The transverse error value is 2.56 h, which decreases 32.34 and 32.58 MWs respectively. The result shows that the proposed method can effectively improve the short-term power prediction accuracy of wind power generation.
【作者单位】：新疆大学电气工程学院;国网新疆电力公司;克拉玛依理工学院筹建办公室;奥尔堡大学工程与科学学院;
【基金】：国家自然科学基金项目(51267020) 国家国际科技合作专项资助(2013DFG61520) 高等学校博士学科点专项科研基金博导类联合资助项目(20126501110003)~~
【分类号】：TM614

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