山东大学学报(工学版)
山東大學學報(工學版)
산동대학학보(공학판)
JOURNAL OF SHANDONG UNIVERSITY(ENGINEERING SCIENCE)
2014年
1期
85-89
,共5页
麻常辉%冯江霞%蒋哲%武乃虎%吕晓禄
痳常輝%馮江霞%蔣哲%武迺虎%呂曉祿
마상휘%풍강하%장철%무내호%려효록
风力发电%风速%风电功率%时间序列%神经网络
風力髮電%風速%風電功率%時間序列%神經網絡
풍력발전%풍속%풍전공솔%시간서렬%신경망락
wind power generation%wind speed%wind power%time series%BP-ANN
为克服风速与风电功率之间的非线性关系对预测精度的影响,建立了基于时间序列法和神经网络法的改进预测模型。用时间序列法建立风速预测模型;利用神经网络法建立风速-风电功率模型,并以风速预测数据为输入量预测风电功率。以某风电场为例,比较分析了该改进模型与传统预测模型的平均绝对误差和相关系数,结果表明该改进预测模型可有效提高预测精度。
為剋服風速與風電功率之間的非線性關繫對預測精度的影響,建立瞭基于時間序列法和神經網絡法的改進預測模型。用時間序列法建立風速預測模型;利用神經網絡法建立風速-風電功率模型,併以風速預測數據為輸入量預測風電功率。以某風電場為例,比較分析瞭該改進模型與傳統預測模型的平均絕對誤差和相關繫數,結果錶明該改進預測模型可有效提高預測精度。
위극복풍속여풍전공솔지간적비선성관계대예측정도적영향,건립료기우시간서렬법화신경망락법적개진예측모형。용시간서렬법건립풍속예측모형;이용신경망락법건립풍속-풍전공솔모형,병이풍속예측수거위수입량예측풍전공솔。이모풍전장위례,비교분석료해개진모형여전통예측모형적평균절대오차화상관계수,결과표명해개진예측모형가유효제고예측정도。
To solve the problem that non-linear relationship between wind speed and wind power could amplify predic-tion error, the improved model for wind speed and wind power forecasting in short term was proposed based on time se-ries and back propagation artificial neural network ( BP-ANN) .First, the time series model was built to forecast wind speed.Then the BP-ANN model of wind speed-to-power was set up and the predicted wind speed was input into the model to obtain wind power.Taking a wind power plant as an example, mean absolute error and correlation index of the improved model and the conventional model were compared, and the result showed that the improved model could im-prove wind power forecasting accuracy.