本文選題：風電功率預測　切入點：橫向誤差　出處：《電網(wǎng)技術》2015年10期 　論文類型：期刊論文

【摘要】：目前風電預測功率精度偏低,評估指標常用縱向誤差,很少針對橫向誤差(延遲或超前時間)進行統(tǒng)計。提出了基于橫、縱向誤差平移修正的風電預測精度改善方法,給出用于風電功率預測的不變趨勢功率持續(xù)時間的概念,并將風電場日前功率預測曲線和實際功率曲線劃分為不變趨勢功率增加段、降低段和保持段3種模式。建立了各不變趨勢持續(xù)時間的計算模型,采用概率統(tǒng)計法獲得預測時間值與實際時間值之間的偏差值及滯后或超前方向,利用平移法和插值法聯(lián)合橫縱向誤差修正日前功率預測誤差。應用上述方法對新疆某地區(qū)風電功率預測曲線進行仿真計算,結果如下:該地區(qū)風電功率預測橫向誤差為3.78 h,方向為超前,縱向絕對誤差值為40.05 MW;采用平移插值修正后,橫向誤差值為2.56 h,降低了32.34%,縱向誤差值為32.58 MW,降低了18.65%。從而表明該方法可以有效提高風電短期預測功率精度。
[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.
【作者單位】： 新疆大學電氣工程學院;國網(wǎng)新疆電力公司;克拉瑪依理工學院籌建辦公室;奧爾堡大學工程與科學學院;
【基金】：國家自然科學基金項目(51267020) 國家國際科技合作專項資助(2013DFG61520) 高等學校博士學科點專項科研基金博導類聯(lián)合資助項目(20126501110003)~~
【分類號】：TM614

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本文編號：1620763