Title :
Application of ARMA Model in Ultra-short Term Prediction of Wind Power
Author :
Jianyong Zhang ; Cong Wang
Author_Institution :
Dept. of Math. & Phys., Hohai Univ., Changzhou, China
Abstract :
The randomness of the wind velocity causes the fluctuation of wind power. Therefore, It is necessary to forecast the wind power in a certain time. In this paper, the ultra-short term predication of wind power has been carried out based on the Auto-Regressive-and-Moving-Average (ARMA) model. The wind power was predicted by prediction steps of ARMA in section II. According to the corresponding national standard, the predicted results were evaluated in TABLE I and II, simultaneously, compared with the predicted results of BP neural network in subsection C of section III. Finally, it is found that the ARMA model is more suitable for ultra-short term prediction of wind power.
Keywords :
autoregressive moving average processes; wind power; ARMA model; auto regressive and moving average model; ultra short term prediction; wind power; wind velocity; Accuracy; Analytical models; Mathematical model; Neural networks; Power systems; Predictive models; Wind power generation; ARMA; prediction; wind power;
Conference_Titel :
Computer Sciences and Applications (CSA), 2013 International Conference on
Conference_Location :
Wuhan
DOI :
10.1109/CSA.2013.91