电力系统保护与控制2017，Vol.45Issue(4)：72-79,8.DOI:10.7667/PSPC160284
基于改进EEMD-SE-ARMA的超短期风功率组合预测模型
Wind power ultra short-term model based on improved EEMD-SE-ARMA
摘要
Abstract
In view of the nonlinear and non-stationary characteristics of wind power time series,this paper presents a modified ensemble empirical mode decomposition (MEEMD)-sample entropy (SE)-ARMA wind power ultra short term combined forecasting model.The white noise signal added in the EEMD decomposition is changed to two groups positive and negative white noise signal which have the equal absolute value,and the EMD steps of the decomposition process of MEEMD is improved with the endpoint extension and three piecewise Hermite interpolation,forming a modified EEMD decomposition algorithm (MEEMD).The wind power time series is decomposed into a series of complex wind power generation by MEEMD-SE,and the ARMA forecasting model is built for each different sub sequence,and the final wind power forecast value is obtained.Through numerical analysis and comparison with other forecasting models,the results show that the MEEMD-SE-ARMA combination forecasting model can effectively improve the accuracy of the ultra short term forecasting of wind power generation.关键词
改进的集成经验模态分解/风电预测/样本熵/时间序列/组合预测模型/端点延拓Key words
improved ensemble empirical mode decomposition/wind power prediction/sample entropy/time series/combined prediction model/endpoint extension引用本文复制引用
田波,朴在林,郭丹,王慧..基于改进EEMD-SE-ARMA的超短期风功率组合预测模型[J].电力系统保护与控制,2017,45(4):72-79,8.基金项目
十二五国家科技支撑项目(2012BAJ26B00)This work is supported by National Science & Technology Pillar Program during the 12th Five-year Plan Period (No.2012BAJ26B00). （2012BAJ26B00）
