科技和产业
科技和產業
과기화산업
SCIENCE TECHNOLOGY AND INDUSTRIAL
2014年
4期
143~146
,共null页
王强 汪姚 胡红飒 朱家明
王彊 汪姚 鬍紅颯 硃傢明
왕강 왕요 호홍삽 주가명
风电功率 BP神经网络算法 风电功率预测模型 Mean Absolute Error (MAE)
風電功率 BP神經網絡算法 風電功率預測模型 Mean Absolute Error (MAE)
풍전공솔 BP신경망락산법 풍전공솔예측모형 Mean Absolute Error (MAE)
the wind power;BP neural network algorithm; Mean Absolute Error (MAE) ;the wind power forecasting model;Matlab
针对风电功率的预测,从神经网络的训练仿真入手,综合运用BP神经网络、平均绝对误差MAE等多种方法,建立风电功率预测模型,运用M atlab和Excel软件编程,得到了后续7天中时隔5min和15min的风电功率预测趋势和时隔5min样本数据的预测误差水平相对于15min来说降低了6.349%等结果。
針對風電功率的預測,從神經網絡的訓練倣真入手,綜閤運用BP神經網絡、平均絕對誤差MAE等多種方法,建立風電功率預測模型,運用M atlab和Excel軟件編程,得到瞭後續7天中時隔5min和15min的風電功率預測趨勢和時隔5min樣本數據的預測誤差水平相對于15min來說降低瞭6.349%等結果。
침대풍전공솔적예측,종신경망락적훈련방진입수,종합운용BP신경망락、평균절대오차MAE등다충방법,건립풍전공솔예측모형,운용M atlab화Excel연건편정,득도료후속7천중시격5min화15min적풍전공솔예측추세화시격5min양본수거적예측오차수평상대우15min래설강저료6.349%등결과。
Aimed at the wind power forecasting ,the wind power forecasting model is established based on the training simulation of the neural network via means of the BP neural network algorithm ,MAE ,etc. Through such a model and using Matlab and Excell,we get the wind power forecasting trend at the intervals of 5minutes and 15minutes of the following 7 days and the result that the forecasting error of the sample data at the interval of 5minutes is 6.349% lower than that of 15minutes .