Short term forecasting for wind power based on cluster analysis

被引：0

作者：

Gao, Yang ^{[1
]}

Xing, Jing ^{[1
]}

Xu, Aoran ^{[1
]}

Zhang, Liu ^{[1
]}

Wang, Gang ^{[1
]}

Zou, Quanping ^{[1
]}

机构：

[1] Electric power college, Shenyang Institute of Engineering, Pu Chang Str.18 of Shenbei New Area, Shenyang, Liaoning Province, China

来源：

Computer Modelling and New Technologies | 2014年 / 18卷 / 12期

关键词：

Wind effects - Numerical methods - Weather forecasting - Wind speed - Wind farm;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In order to make full use of historical wind speed information behind the data, according to daily similarity of the wind speed and wind power, short term power forecasting method based on cluster analysis is presented in this paper. Through the original sample data is preprocessed, election history daily data that is similar with characteristic parameters of NWP of forecast day, so as to establish training samples of model. NWP information of forecast day provided by Meteorological Department will be as the characteristic parameters of forecast day, and calculating Euclidean distance between characteristic parameters will be regarded as a basis of similarity measure. Finally forecasting model is founded by adopting similar samples based on cluster. Using NWP data as input parameters, the actual wind power as a target value, many kinds of short-term wind power forecasting model is gained by training. Through the actual wind farm test, forecasting accuracy is improved obviously.

引用

页码：321 / 325

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