广东电力2026，Vol.39Issue(2)：29-40,12.DOI:10.3969/j.issn.1007-290X.2026.02.003
融合VMD与FECAM的日前电价预测研究
Study on Day-ahead Electricity Price Forecasting Based on the Integration of VMD and FECAM
摘要
Abstract
In response to the challenges of frequent fluctuations,strong nonlinearity and drastic extreme value changes in the electricity spot market,this paper proposes an electricity price forecasting model that integrates variational mode decomposition(VMD)and the frequency enhanced channel attention mechanism(FECAM).It firstly decomposes the original electricity price series into multiple intrinsic mode functions with distinct frequency components by using VMD,effectively reducing data non-stationarity.Then,it uses convolutional neural networks(CNN)to extract key features and combines bidirectional long short-term memory network(BiLSTM)to enhance long timing process ability of the model.Finally,by introducing the FECAM,the model's adaptability to critical features is strengthened.The experimental results demonstrate that the proposed model outperforms traditional regression models and other deep learning approaches on datasets from the Australian electricity market,GEFCom2014,and the U.S.PJM market.The model exhibits superior prediction accuracy and demonstrates its applicability in complex electricity market environments.关键词
电价预测/变分模态分解/注意力机制/深度学习/日前电价Key words
electricity price forecasting/variational mode decomposition(VMD)/attention mechanism/deep learning/day-ahead electricity price分类
信息技术与安全科学引用本文复制引用
王骁,周建新,刘培栋,张卓越..融合VMD与FECAM的日前电价预测研究[J].广东电力,2026,39(2):29-40,12.基金项目
华润电力科技项目(K2020-04) （K2020-04）
