气候变化领域集成服务门户(CCPortal): Wind speed forecasting based on model selection, fuzzy cluster, and multi-objective algorithm and wind energy simulation by Betz's theory

CCPortal

DOI	10.1016/j.eswa.2022.116509
	Wind speed forecasting based on model selection, fuzzy cluster, and multi-objective algorithm and wind energy simulation by Betz's theory
	Zhang, Shenghui; Wang, Chen; Liao, Peng; Xiao, Ling; Fu, Tonglin
通讯作者	Wang, C (通讯作者)，Sun Yat Sen Univ, Sch Intelligent Syst Engn, Guangzhou 510006, Peoples R China.
发表日期	2022
ISSN	0957-4174
EISSN	1873-6793
卷号	193
英文摘要	Wind energy is of increasing interest to wind farm administrators as a clean and renewable energy source. Accurate wind speed forecasting and effective wind energy simulation can increase the capability of wind power combined with a grid and decrease the operating cost of wind farms. However, many previous studies have been restricted to wind speed forecasting, ignoring wind energy simulations. Thus, grid management cannot effectively estimate the power production of wind farms and leads to an increase in the abandonment wind rate in wind farms. In this study, a wind farm auxiliary management system is developed, which includes two modules: wind speed forecasting and wind energy simulation. In the wind speed forecasting module, first, a data mining algorithm is used to analyze different features of wind speed time series data in a wind farm. Subsequently, a feature selection algorithm is used to determine the representative wind speed time series of the wind farm, and it is combined with a data preprocessing method to effectively eliminate the noise of the original wind speed time series. Second, six hybrid neural network forecasting models based on a modified multi-objective algorithm are established to forecast wind speed. Finally, they are combined with a model selection strategy to yield the best forecasting value for each time point. In the wind energy simulation module, using Betz's theory, the physical transformation process of a wind turbine is estimated to determine the range of wind power generation.
关键词	TIME-SERIES ARTIFICIAL-INTELLIGENCE ARMA MODEL SYSTEM OPTIMIZATION PREDICTION STRATEGY DENSITY
英文关键词	Modified multi-objective algorithm; Fuzzy c-means cluster; Model selection strategy; Betz's theory; Wind speed forecasting
语种	英语
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS记录号	WOS:000748635600002
来源期刊	EXPERT SYSTEMS WITH APPLICATIONS
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/254794
作者单位	[Zhang, Shenghui] Univ Macau, State Key Lab Internet Things Smart City, Macau 999078, Peoples R China; [Zhang, Shenghui] Univ Macau, Dept Comp & Informat Sci Org, Macau 999078, Peoples R China; [Wang, Chen] Sun Yat Sen Univ, Sch Intelligent Syst Engn, Guangzhou 510006, Peoples R China; [Liao, Peng] Lanzhou Univ, Sch Math & Stat, Lanzhou 730000, Peoples R China; [Xiao, Ling] Xuzhou Univ Technol, Sch Methemat & Stat, Xuzhou 221018, Jiangsu, Peoples R China; [Fu, Tonglin] LongDong Univ, Sch Math & Stat, Qingyang 745000, Peoples R China; [Fu, Tonglin] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Shapotou Desert Res & Expt Stn, Lanzhou 730000, Peoples R China; [Fu, Tonglin] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Shenghui,Wang, Chen,Liao, Peng,et al. Wind speed forecasting based on model selection, fuzzy cluster, and multi-objective algorithm and wind energy simulation by Betz's theory[J]. 中国科学院西北生态环境资源研究院,2022,193.
APA	Zhang, Shenghui,Wang, Chen,Liao, Peng,Xiao, Ling,&Fu, Tonglin.(2022).Wind speed forecasting based on model selection, fuzzy cluster, and multi-objective algorithm and wind energy simulation by Betz's theory.EXPERT SYSTEMS WITH APPLICATIONS,193.
MLA	Zhang, Shenghui,et al."Wind speed forecasting based on model selection, fuzzy cluster, and multi-objective algorithm and wind energy simulation by Betz's theory".EXPERT SYSTEMS WITH APPLICATIONS 193(2022).