Dynamic Neural Network Based Very Short-Term Wind Speed Forecasting

被引：9
|
作者：
Babu, Ramesh N. [1 ]
Arulmozhivarman, P. [1 ]
机构：
[1] VIT Univ, Sch Elect Engn, Vellore 632014, Tamil Nadu, India
来源：
WIND ENGINEERING | 2014年 / 38卷 / 02期
关键词：
NARX; Back propagation; Forecast; Wind speed;
D O I：
10.1260/0309-524X.38.2.121
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
In this paper, the nonlinear autoregressive model with exogenous inputs (NARX) is proposed for wind speed forecast. Forecasting wind speed is a challenging task in wind energy research domain which influences the dynamic control of wind turbine and for system scheduling. The aim of this study is to obtain suitable forecast model for wind speed with time series input variables such as wind direction, humidity, pressure and time. The meteorological data observed with 15 minute time intervals is used for the model and the performance is evaluated and compared with the back propagation neural network (BPNN). The result shows that the proposed model outperforms the BPNN based on the metrics used.
引用
收藏
页码：121 / 128
页数：8
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