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A combination predicting methodology based on T-LSTNet_Markov for short-term wind power prediction

文献类型：期刊论文

作者Wang, Yongsheng3,4; Wu, Yuhao3; Xu, Hao3,4; Chen, Zhen3,4; Gao, Jing1,5; Xu, ZhiWei2,3,4; Li, Leixiao3,4
刊名NETWORK-COMPUTATION IN NEURAL SYSTEMS
出版日期2023-05-20
页码23
ISSN号0954-898X
关键词Wind power forecast T-LSTNet_markov model Deep learning Time series analysis
DOI10.1080/0954898X.2023.2213756
英文摘要Wind power has been valued by countries for its renewability and cleanness and has become most of the focus of energy development in all countries. However, due to the uncertainty and volatility of wind power generation, making the grid-connected wind power system presents some serious challenges. Improving the accuracy of wind power prediction has become the focus of current research. Therefore, this paper proposes a combined short-term wind power prediction model based on T-LSTNet_markov to improve prediction accuracy. First, perform data cleaning and data preprocessing operations on the original data. Second, forecast using T-LSTNet model in original wind power data. Finally, calculate the error between the forecast value and the actual value. The k-means++ method and Weighted Markov process are used to correct errors and to get the result of the final prediction. The data that are collected from a wind farm in Inner Mongolia Autonomous Region, China, are selected as a case study to demonstrate the effectiveness of the proposed combined models. The empirical results show that the prediction accuracy is further improved after correcting errors.
资助项目Department of Science and Technology of Inner Mongolia[2020CG0073] ; National Natural Science Foundation of China[61962045] ; Natural Science Foundation of Inner Mongolia[2019MS03014] ; Research Program of Science and Technology at Universities of Inner Mongolia Autonomous Region[NJZY21321] ; Science and Technology Major Project of Inner Mongolia[2019ZD016]
WOS研究方向Computer Science ; Engineering ; Neurosciences & Neurology
语种英语
出版者TAYLOR & FRANCIS INC
WOS记录号WOS:000996919800001
源URL[http://119.78.100.204/handle/2XEOYT63/21473]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Wu, Yuhao
作者单位1.Inner Mongolia Agr Univ, Coll Comp & Informat Engn, Hohhot, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
3.Inner Mongolia Univ Technol, Coll Data Sci & Applicat, Hohhot, Peoples R China
4.Res Ctr Big Data Based Software Serv, Inner Mongolia Autonomous Reg Engn & Technol, Hohhot, Peoples R China
5.Inner Mongolia Autonomous Reg Key Lab Big Data Res, Hohhot, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Yongsheng,Wu, Yuhao,Xu, Hao,et al. A combination predicting methodology based on T-LSTNet_Markov for short-term wind power prediction[J]. NETWORK-COMPUTATION IN NEURAL SYSTEMS,2023:23.
APA Wang, Yongsheng.,Wu, Yuhao.,Xu, Hao.,Chen, Zhen.,Gao, Jing.,...&Li, Leixiao.(2023).A combination predicting methodology based on T-LSTNet_Markov for short-term wind power prediction.NETWORK-COMPUTATION IN NEURAL SYSTEMS,23.
MLA Wang, Yongsheng,et al."A combination predicting methodology based on T-LSTNet_Markov for short-term wind power prediction".NETWORK-COMPUTATION IN NEURAL SYSTEMS (2023):23.

入库方式： OAI收割

来源：计算技术研究所

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