Very Short-Term Wind Power Forecasting Based on SVM-Markov

被引：0

作者：

Jiang, Shunhui ^{[1
]}

Fang, Ruiming ^{[1
]}

Wang, Li ^{[1
]}

Peng, Changqing ^{[1
]}

机构：

[1] Huaqiao Univ, Coll Informat Sci & Engn, Xiamen 361021, Peoples R China

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCES IN ENERGY, ENVIRONMENT AND CHEMICAL ENGINEERING | 2015年 / 23卷

关键词：

Very short-term forecasting; SVM; Markov chain model; the confidence interval;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Very short-term forecasting of wind power is important to scheduling staff's planning and wind turbine control. This paper has established a combined forecasting model based on Markov chain and support vector machine (SVM). Firstly, the SVM is used to model for wind power. Then, transition probability matrix is made based on Markov chain to modify for SVM prediction. Finally, the prediction confidence interval of combination forecasting model is given by method of fluctuation confidence interval. Verified by an example of a wind farm indicating that the combination forecasting model is better than a single SVM model on a variety of error indicators.

引用

页码：130 / 134

页数：5

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