Wind power day-ahead prediction with cluster analysis of NWP

被引：108
|
作者：
Dong, Lei [1 ]
Wang, Lijie [2 ]
Khahro, Shahnawaz Farhan [1 ]
Gao, Shuang [1 ]
Liao, Xiaozhong [1 ]
机构：
[1] Beijing Inst Technol, Sch Automat, 5 Zhongguancun South St, Beijing 100081, Peoples R China
[2] Beijing Informat Sci & Technol, Dept Elect Engn, 12 Xiaoying East St, Beijing, Peoples R China
来源：
RENEWABLE & SUSTAINABLE ENERGY REVIEWS | 2016年 / 60卷
关键词：
Wind power prediction; Numerical weather prediction; Cluster analysis; Modeling; Daily similarity; SPEED; FORECASTS;
D O I：
10.1016/j.rser.2016.01.106
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
The selection of training data for establishing a model directly affects the prediction precision. Wind power has the characteristic of daily similarity. The corresponding meteorological data also has the characteristic of daily similarity. This paper proposes a new model with cluster analysis of the numerical weather prediction information. The similar day with the predicted day is searched as training sample to a generalized regression neural network model. The numerical weather prediction data and actual wind power data from a wind farm are used in this study to test the model. The prediction results show that correct cluster analysis method is a useful tool in day-ahead wind power prediction. (C) 2016 Published by Elsevier Ltd.
引用
收藏
页码：1206 / 1212
页数：7
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