A Short-Term Load Forecasting Method Based on GRU-CNN Hybrid Neural Network Model
Wu, Lizhen; Kong, Chun; Hao, Xiaohong; Chen, Wei
2020-03-21
Source PublicationMATHEMATICAL PROBLEMS IN ENGINEERING
ISSN1024-123X
Volume2020
AbstractShort-term load forecasting (STLF) plays a very important role in improving the economy and stability of the power system operation. With the smart meters and smart sensors widely deployed in the power system, a large amount of data was generated but not fully utilized, these data are complex and diverse, and most of the STLF methods cannot well handle such a huge, complex, and diverse data. For better accuracy of STLF, a GRU-CNN hybrid neural network model which combines the gated recurrent unit (GRU) and convolutional neural networks (CNN) was proposed; the feature vector of time sequence data is extracted by the GRU module, and the feature vector of other high-dimensional data is extracted by the CNN module. The proposed model was tested in a real-world experiment, and the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the GRU-CNN model are the lowest among BPNN, GRU, and CNN forecasting methods; the proposed GRU-CNN model can more fully use data and achieve more accurate short-term load forecasting.
DOI10.1155/2020/1428104
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[51467009] ; Basic Research Innovation Group Project of Gansu Province[18JR3RA133]
WOS Research AreaEngineering ; Mathematics
WOS SubjectEngineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
WOS IDWOS:000522946500001
PublisherHINDAWI LTD
Document Type期刊论文
Identifierhttp://ir.lut.edu.cn/handle/2XXMBERH/76639
Collection电气工程与信息工程学院
Corresponding AuthorChen, Wei
AffiliationLanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Gansu, Peoples R China
First Author AffilicationColl Elect & Informat Engn
Corresponding Author AffilicationColl Elect & Informat Engn
First Signature AffilicationColl Elect & Informat Engn
Recommended Citation
GB/T 7714
Wu, Lizhen,Kong, Chun,Hao, Xiaohong,et al. A Short-Term Load Forecasting Method Based on GRU-CNN Hybrid Neural Network Model[J]. MATHEMATICAL PROBLEMS IN ENGINEERING,2020,2020.
APA Wu, Lizhen,Kong, Chun,Hao, Xiaohong,&Chen, Wei.(2020).A Short-Term Load Forecasting Method Based on GRU-CNN Hybrid Neural Network Model.MATHEMATICAL PROBLEMS IN ENGINEERING,2020.
MLA Wu, Lizhen,et al."A Short-Term Load Forecasting Method Based on GRU-CNN Hybrid Neural Network Model".MATHEMATICAL PROBLEMS IN ENGINEERING 2020(2020).
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