基于小波变换和时间序列法考虑随机分量的短期风速预测  

Short-term Wind Speed Prediction Based on Wavelet Transform and Time Series Method and Random Components

作　　者：贾彦[1,2] 汪尧 王骥飞 赵萌 张驰[1] 李文雄 JIA Yan;WANG Yao;WANG Ji-fei;ZHAO Meng;ZHANG Chi;LI Wen-xiong(College of Energy and Power Engineering,Inner Mongolia University of Technology,Hohhot 010051,China;Ministry of Education Key Laboratory of Wind Energy Utilization Technology,Hohhot 010051,China)

机构地区：[1]内蒙古工业大学能源与动力工程学院,内蒙古呼和浩特010051 [2]风能太阳能利用技术教育部重点实验室,内蒙古呼和浩特010051

出　　处：《内蒙古工业大学学报（自然科学版）》2019年第2期115-121,共7页Journal of Inner Mongolia University of Technology：Natural Science Edition

基　　金：内蒙古自治区科技厅科技计划项目(201601064);风能太阳能利用技术省部共建教育部重点实验室开放基金(201507)

摘　　要：为提高短期风速预测的准确性,本文结合小波变换和时间序列法,考虑随机分量进行短期风速预测.利用小波变换对风速时间序列分层,将高频变化的风速时间序列利用自回归滑动平均模型(ARMA)进行预测,低频变化的风速时间序列利用持续法进行预测,最后将预测结果叠加并通过随机阵列对结果进行修正.通过实例验证以及与时间序列方法进行对比,结果证明该方法的预测精度和预测稳定性都有所提高.In order to improve the accuracy of short-term wind speed prediction,this paper combines the wavelet transformation and time series method and takes random components into consideration for short-term wind speed prediction.The wavelet transformation was used to stratify the wind speed time series.After that,the high-frequency-varied wind speed time series were predicted by time series Autoregressive Moving Average Model (ARMA),and the low-frequency-varied wind speed time series were predicted by time series continuous method.The final prediction results were the combination of the above two components,and they were further refined by a method of random array.The example verification and the comparison with the prediction by time series method show that the prediction accuracy and prediction stability of the method are significantly improved.

关 键 词：小波变换 时间序列ARMA 时间序列持续法 随机分量 风速预测 

分 类 号：TK89[动力工程及工程热物理—流体机械及工程]