基于集合经验模态分解和特征选择极端学习机的风速预测

被引：11

作者：

冯义 ^{[1
]}

刘慧文 ^{[1
]}

张宝平 ^{[1
]}

张宝栋 ^{[2
]}

阮亮 ^{[3
]}

机构：

[1] 国网电动汽车有限公司

[2] 国网山东省电力公司济南供电公司

[3] 华北电力大学经济管理学院

来源：

智慧电力 | 2018年 / 46卷 / 12期

关键词：

集合经验模态分解; 随机森林; 特征选择; 极端学习机; 短期风速预测;

D O I：

暂无

中图分类号：

TM315 [风力发电机];

学科分类号：

080802 [电力系统及其自动化];

摘要：

提出一种集合经验模态分解、随机森林和极端学习机建模的短期风速预测方法。首先,引入集合经验模态分解将原始风速数据分解成代表不同波动特征的分量,剔除不规则的分量;然后,对保留分量逐一建模,构建随机森林特征选择算法,根据重要性来提取模型的特征输入;最后,建立基于特征选择和极端学习机的风速分量预测模型进行预测,综合分量预测结果得出最终预测结果。

引用

页码：30 / 37

页数：8

共 19 条

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[2]

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