电力系统保护与控制2011，Vol.39Issue(3)：46-51,6.
基于经验模态分解和基因表达式程序设计的电力系统短期负荷预测
Short-term load forecasting based on empirical mode decomposition and gene expression programming
范新桥 1朱永利 1尹金良1
作者信息
- 1. 华北电力大学电气与电子工程学院,北京,102206
- 折叠
摘要
Abstract
A forecasting method based on Empirical Mode Decomposition (EMD)and Gene Expression Programming (GEP) that's called EMD & GEP here is presented and applied to short-term load forecasting. Firstly, the load samples are handled in order to eliminate the pseudo-data, and the intrinsic mode functions (IMFs) and the residue of different frequency bands are obtained according to EMD. Then the corresponding load series of the same time but different days in the IMFs and the residue are chosen as the training samples. By means of the flexible expressive capacity of GEP, the models of different time points in each IMF and the residue are forecasted according to time-sharing. Finally, the ultimate forecasting result is obtained by reconstructing the forecasting results of each IMF and the residue. The method of EMD overcomes the shortcomings that it's difficult to select proper wavelet function for wavelet transform, and the final result indicates that the IMFs can reflect the characteristic of load. After comparing with the results forecasted by means of combination of Wavelet and GEP, it proves that the effect of the forecasting method of EMD&GEP in short-term load forecasting is better.关键词
短期负荷预测/经验模态分解/基因表达式程序设计/电力系统Key words
short-term load forecasting/ empirical mode decomposition/ gene expression programming/ power system分类
信息技术与安全科学引用本文复制引用
范新桥,朱永利,尹金良..基于经验模态分解和基因表达式程序设计的电力系统短期负荷预测[J].电力系统保护与控制,2011,39(3):46-51,6.
