CSpace
A novel machine learning-based electricity price forecasting model based on optimal model selection strategy
Yang, Wendong1,2; Sun, Shaolong3; Hao, Yan4; Wang, Shouyang5,6,7
2022
Source PublicationENERGY
ISSN0360-5442
Volume238Pages:14
AbstractCurrent electricity price forecasting models rely on only simple hybridizations of data preprocessing and optimization methods while ignoring the significance of adaptive data preprocessing and effective optimization and selection strategies to obtain optimal models that improve the forecasting performance. To solve these problems, this study develops an improved electricity price forecasting model that offers the advantages of adaptive data preprocessing, advanced optimization method, kernel-based model, and optimal model selection strategy. Specifically, the adaptive parameter-based variational mode decomposition technology is proposed to provide desirable data preprocessing results, and a leave-one-out optimization strategy based on the chaotic sine cosine algorithm is proposed and applied to develop optimal kernel-based extreme learning machine models. In addition, a newly proposed optimal model selection strategy is applied to determine the developed model that provides the most desirable forecasting result. Numerical results show that the developed model's performance metrics were best, and the average values of mean absolute error, root mean square error, mean absolute percentage error, index of agreement, and Theil's inequality coefficient in four datasets are 0.5121, 0.7607, 0.5722%, 0.9997 and 0.0041, respectively, which imply that the developed model is a promising, applicable and effective electricity price forecasting technique in the real electricity market. (c) 2021 Elsevier Ltd. All rights reserved.
KeywordElectricity price Forecasting Hybrid model Model selection Kernel-based extreme learning machine
DOI10.1016/j.energy.2021.121989
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Founda-tion of China[71988101] ; National Natural Science Founda-tion of China[72101197] ; National Natural Science Founda-tion of China[72101138] ; Humanities and Social Science Fund of Ministry of Ed-ucation of the People's Republic of China[21YJCZH198]
WOS Research AreaThermodynamics ; Energy & Fuels
WOS SubjectThermodynamics ; Energy & Fuels
WOS IDWOS:000702790700012
PublisherPERGAMON-ELSEVIER SCIENCE LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/59327
Collection中国科学院数学与系统科学研究院
Corresponding AuthorSun, Shaolong
Affiliation1.Shandong Univ Finance & Econ, Sch Management Sci & Engn, Jinan 250014, Shandong, Peoples R China
2.Shandong Univ Finance & Econ, Inst Marine Econ & Management, Jinan, Shandong, Peoples R China
3.Xi An Jiao Tong Univ, Sch Management, Xian 710049, Shaanxi, Peoples R China
4.Shandong Normal Univ, Business Sch, Jinan 250014, Shandong, Peoples R China
5.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
6.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China
7.Chinese Acad Sci, Ctr Forecasting Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Yang, Wendong,Sun, Shaolong,Hao, Yan,et al. A novel machine learning-based electricity price forecasting model based on optimal model selection strategy[J]. ENERGY,2022,238:14.
APA Yang, Wendong,Sun, Shaolong,Hao, Yan,&Wang, Shouyang.(2022).A novel machine learning-based electricity price forecasting model based on optimal model selection strategy.ENERGY,238,14.
MLA Yang, Wendong,et al."A novel machine learning-based electricity price forecasting model based on optimal model selection strategy".ENERGY 238(2022):14.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Yang, Wendong]'s Articles
[Sun, Shaolong]'s Articles
[Hao, Yan]'s Articles
Baidu academic
Similar articles in Baidu academic
[Yang, Wendong]'s Articles
[Sun, Shaolong]'s Articles
[Hao, Yan]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Yang, Wendong]'s Articles
[Sun, Shaolong]'s Articles
[Hao, Yan]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.