An overview of deterministic and probabilistic forecasting methods of wind energy

被引:27
|
作者
Xie, Yuying [1 ,2 ,3 ,4 ]
Li, Chaoshun [1 ,2 ]
Li, Mengying [2 ,3 ,4 ]
Liu, Fangjie [1 ]
Taukenova, Meruyert [1 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Civil & Hydraul Engn, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, China EU Inst Clean & Renewable Energy, Wuhan 430074, Peoples R China
[3] Hong Kong Polytech Univ, Res Inst Smart Energy, Dept Mech Engn, Hong Kong, Peoples R China
[4] Hong Kong Polytech Univ, Dept Mech Engn, Kowloon, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
EMPIRICAL MODE DECOMPOSITION; PARTICLE SWARM OPTIMIZATION; SINGULAR SPECTRUM ANALYSIS; EXTREME LEARNING-MACHINE; WAVELET PACKET DECOMPOSITION; ARTIFICIAL NEURAL-NETWORKS; TERM-MEMORY NETWORK; CORAL-REEFS OPTIMIZATION; DATA-PROCESSING STRATEGY; SPEED PREDICTION;
D O I
10.1016/j.isci.2022.105804
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In recent years, a variety of wind forecasting models have been developed, prompting necessity to review the abundant methods to gain insights of the state-of-the-art development status. However, existing literature reviews only focus on a subclass of methods, such as multi-objective optimization and machine learning methods while lacking the full particulars of wind forecasting field. Furthermore, the classification of wind forecasting methods is unclear and incomplete, especially considering the rapid development of this field. Therefore, this article aims to provide a systematic review of the existing deterministic and probabilistic wind forecasting methods, from the perspectives of data source, model evaluation framework, technical background, theoretical basis, and model performance. It is expected that this work will provide junior researchers with broad and detailed information on wind forecasting for their future development of more accurate and practical wind forecasting models.
引用
收藏
页数:35
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