Review of Wind Power Forecasting Methods: From Multi-spatial and temporal Perspective

被引:0
|
作者
Jiang, Zhaoyu [1 ]
Jia, Qing-Shan [1 ]
Guan, Xiaohong [1 ,2 ]
机构
[1] Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol, Dept Automat, CFINS, Beijing 100084, Peoples R China
[2] Xi An Jiao Tong Univ, MOE KLINNS Lab, Xian 710049, Shaanxi, Peoples R China
来源
PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017) | 2017年
基金
中国国家自然科学基金;
关键词
Wind power forecasting; Forecast method; Temporal scale; Spatial scale; Review; PARTICLE SWARM OPTIMIZATION; ARTIFICIAL NEURAL-NETWORKS; SPEED PREDICTION; GAUSSIAN-PROCESSES; MODEL; ENSEMBLE; STRATEGY; REGRESSION; SELECTION; SYSTEM;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Wind power is one of the most popular renewables and occupies a great proportion in the total capacity of the grid system. Secure operations of the grid system such as scheduling and dispatching dependent much on the prediction accuracy of power generation. This paper reviews wind power forecasting methods in multi-spatial scales and multi-temporal scales. In different spatial scales, methods for a single turbine, a wind farm, and even a large wind power generation area are considered in three parts respectively. In each part, firstly, forecasting methods are divided into methods with only historical wind information and methods with additional meteorological information, and then, classified up to four different temporal scales. Discussion about the similarity and discrepancy of these methods are also presented at the end of each part. Finally, this paper gives two examples of real applications where wind power forecasting methods are significant.
引用
收藏
页码:10576 / 10583
页数:8
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