电力建设2025，Vol.46Issue(4)：49-57,9.DOI:10.12204/j.issn.1000-7229.2025.04.005
基于集成图卷积变分变换器的电力负荷数据补全方法
Power Load Data Completion Method Based on Integrated Graph Convolutional Variational Transformer
摘要
Abstract
[Objective]With the development of power systems and continuous expansion of energy systems,massive load power data have been generated.However,missing data are inevitable in the collection and transmission of power data,which greatly restricts the development of system-coordination optimization and advanced data applications.[Methods]To this end,this paper proposes a new power load missing data completion model based on an integrated graph convolutional variational transformer(IGCVT)network.The IGCVT model aggregates an improved graph convolutional network(GCN)and Transformer model using the variational auto-encoder(VAE)architecture.The raw data are processed by the GCN to learn spatial features and deeply mine spatial dependencies;the hidden layer data are reconstructed by the VAE to more effectively restore data distribution characteristics;and the temporal autocorrelation information of the sequence is mined based on the Transformer model.In addition,an improved whale optimization algorithm(WOA)is introduced to optimize the network model hyperparameters and improve the completion accuracy and applicability of the model.Simultaneously,to solve the problem of large errors in the completion of extreme change points of power load data,a two-way data completion method is adopted to make full use of the data information before and after the missing points.[Results]Experimental results show that,compared with the baseline model,the RMSE index is improved by 24.3%,44.0%,and 47.9%,which verifies the superiority of the proposed method.[Conclusions]The results show that the proposed method provides a feasible solution to the problem of missing power load data and is expected to further expand the application scope of the model.关键词
数据补全/图卷积网络/Transformer模型/电力负荷数据Key words
data imputation/graph convolutional networks/transformer model/power load data分类
动力与电气工程引用本文复制引用
严莉,呼海林,史磊,吴钦政,吕天光,徐英东,张闻彬,王高洲..基于集成图卷积变分变换器的电力负荷数据补全方法[J].电力建设,2025,46(4):49-57,9.基金项目
国网山东省电力公司科技项目(52062723000A) This work is supported by State Grid Shandong Electric Power Company Research Program(No.52062723000A). （52062723000A）
