电测与仪表2017，Vol.54Issue(16)：20-24,5.
基于邻域KNN算法的风电功率短期预测模型
Short-term wind power prediction model based on KNN algorithm considering neighbors′ density
朱念芳 1林善明1
作者信息
- 1. 河海大学 物联网工程学院,江苏 常州 213000
- 折叠
摘要
Abstract
The overall operation and the voltage stability of power grid network are likely to be affected by the fluctuations of wind power.High accuracy of short-term wind power prediction can guarantee the stability and safety of power supply system.This paper proposes a KNN algorithm considering neighbors′ density on the basis of KNN algorithm, applying to short-term wind power prediction.The KNN algorithm considering neighbors′ density, firstly identifies training samples within the given domain of testing object and figures out density distribution of the training samples in each dimension;secondly, this algorithm calculates the value of K, which dynamically changes at different times;finally, the test object is classified according to the rules of KNN algorithm.Taking a wind farm in Changzhou as an example, its historical data was analyzed and then predictions were made through the KNN algorithm considering neighbors′ density, proving accuracy and validity of the algorithm.关键词
邻域KNN算法/风力发电/短期功率预测Key words
KNN algorithm considering neighbors density/wind power generation/short-term power prediction分类
信息技术与安全科学引用本文复制引用
朱念芳,林善明..基于邻域KNN算法的风电功率短期预测模型[J].电测与仪表,2017,54(16):20-24,5.
