A hybrid statistical method to predict wind speed and wind power

被引:193
|
作者
Liu, Hui [1 ]
Tian, Hong-Qi [1 ]
Chen, Chao [2 ]
Li, Yan-fei [1 ]
机构
[1] Cent S Univ, Key Lab Traff Safety Track, Minist Educ, Changsha 410075, Hunan, Peoples R China
[2] Monash Univ, Dept Mech & Aerosp Engn, Melbourne, Vic 3168, Australia
关键词
Wind power; Wind speed; Wind farms; Optimization algorithm; Forecasting; GENERATION; OAXACA; MODEL;
D O I
10.1016/j.renene.2009.12.011
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Accurate forecasting of wind speed and wind power is important for the safety of renewable energy utilization. Compared with physical methods, statistical methods are usually simpler and more suitable for small farms. Based on the methods of wavelet and classical time series analysis, a new short-term forecasting method is proposed. Simulation upon actual time data shows that: (1) the mean relative error in multi-step forecasting based on the proposed method is small, which is better than classical time series method and BP network method; (2) the proposed method is robust in dealing with jumping data; and (3) the proposed method is applicable to both wind speed and wind power forecasting. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1857 / 1861
页数:5
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