电力信息与通信技术2026，Vol.24Issue(1)：45-54,10.DOI:10.16543/j.2095-641x.electric.power.ict.2026.01.05
基于改进BERT的多头自注意力非侵入式负荷分解方法
Non-intrusive Load Decomposition Method Based on Improved BERT With Multi-head Self-attention
摘要
Abstract
To address the challenges of inadequate load feature extraction and insufficient decomposition accuracy in non-intrusive load monitoring(NILM)methods,this paper proposes a multi-head self-attention-based approach named frequency and temporal attention-BERT(FAT-BERT),which leverages an enhanced bidirectional encoder representations from transformers(BERT)architecture.First,the time-domain data are converted into frequency-domain representations via Fourier transform,while multi-scale convolutional layers are adopted to comprehensively extract temporal and spectral features of load signals,thereby strengthening the model's capability to characterize diverse load signatures.Second,a frequency-enhanced attention mechanism is integrated into the multi-head self-attention framework to amplify the model's awareness of frequency components in sequential data,which effectively refines the representation of complex load patterns.Concurrently,localized self-attention is incorporated into the modified BERT architecture to eliminate redundant global computations and accelerate operational efficiency.Furthermore,residual connections combined with regularization techniques are implemented to stabilize the training process and enhance overfitting resistance.Extensive experimental evaluations conducted on the REDD and UK-DALE benchmark datasets demonstrate the superior performance of the proposed method.The results quantitatively confirm significant improvements in decomposition accuracy and computational efficiency compared to state-of-the-art baselines,validating the practical effectiveness of FAT-BERT in NILM applications.关键词
非侵入式负荷监测/负荷分解/改进BERT模型/多头自注意力机制/频率注意力Key words
non-intrusive load monitoring/load decomposition/improved BERT model/multi-head self-attention mechanism/frequency attention分类
信息技术与安全科学引用本文复制引用
孙晓晴,李元诚,王庆乐..基于改进BERT的多头自注意力非侵入式负荷分解方法[J].电力信息与通信技术,2026,24(1):45-54,10.基金项目
国家自然科学基金资助项目(62471180). （62471180）
