基于MEEMD-KELM的短期风电功率预测

FM614; 风电功率时序信号是间歇性、波动性的非平稳信号,信号的平稳化处理是风电功率预测的关键.针对EEMD在分解风功率时序信号时存在模态混淆、伪分量和较大的重构误差等问题,将MEEMD用于风功率信号分解并与KELM模型相结合,提出了基于MEEMD-KELM的风电功率短期预测方法.该方法采用CEEMD将原始信号按频率高低依次分解,检测分量的排列熵值,通过熵值判断异常分量信号并将其从原始信号中剔除,再对分离后的信号进行EMD分解,得到的若干个IMF分量分别通过KELM模型进行组合预测.以上海某风场为例进行仿真实验,并与传统方法进行对比,结果表明该方法预测精度更优且更具稳定性....

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Published in电测与仪表 Vol. 57; no. 21; pp. 92 - 98
Main Authors 赵睿智, 丁云飞
Format Journal Article
LanguageChinese
Published 上海电机学院电气学院,上海201306 10.11.2020
Subjects
排列熵
KELM
MEEMD
模态混淆
风电功率预测
Online AccessGet full text
ISSN1001-1390
DOI10.19753/j.issn1001-1390.2020.21.013

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Abstract FM614; 风电功率时序信号是间歇性、波动性的非平稳信号,信号的平稳化处理是风电功率预测的关键.针对EEMD在分解风功率时序信号时存在模态混淆、伪分量和较大的重构误差等问题,将MEEMD用于风功率信号分解并与KELM模型相结合,提出了基于MEEMD-KELM的风电功率短期预测方法.该方法采用CEEMD将原始信号按频率高低依次分解,检测分量的排列熵值,通过熵值判断异常分量信号并将其从原始信号中剔除,再对分离后的信号进行EMD分解,得到的若干个IMF分量分别通过KELM模型进行组合预测.以上海某风场为例进行仿真实验,并与传统方法进行对比,结果表明该方法预测精度更优且更具稳定性.
AbstractList FM614; 风电功率时序信号是间歇性、波动性的非平稳信号,信号的平稳化处理是风电功率预测的关键.针对EEMD在分解风功率时序信号时存在模态混淆、伪分量和较大的重构误差等问题,将MEEMD用于风功率信号分解并与KELM模型相结合,提出了基于MEEMD-KELM的风电功率短期预测方法.该方法采用CEEMD将原始信号按频率高低依次分解,检测分量的排列熵值,通过熵值判断异常分量信号并将其从原始信号中剔除,再对分离后的信号进行EMD分解,得到的若干个IMF分量分别通过KELM模型进行组合预测.以上海某风场为例进行仿真实验,并与传统方法进行对比,结果表明该方法预测精度更优且更具稳定性.
Author 丁云飞
赵睿智
AuthorAffiliation 上海电机学院电气学院,上海201306
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Zhao Ruizhi
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KELM
MEEMD
模态混淆
风电功率预测
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Title 基于MEEMD-KELM的短期风电功率预测
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