气候变化领域集成服务门户(CCPortal): Wind speed forecasting based on multi-objective grey wolf optimisation algorithm, weighted information criterion, and wind energy conversion system: A case study in Eastern China

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DOI	10.1016/j.enconman.2021.114402
	Wind speed forecasting based on multi-objective grey wolf optimisation algorithm, weighted information criterion, and wind energy conversion system: A case study in Eastern China
	Wang, Chen; Zhang, Shenghui; Xiao, Ling; Fu, Tonglin
通讯作者	Zhang, SH (通讯作者)，Univ Macau, Dept Comp & Informat Sci Org, State Key Lab Internet Things Smart City, Macau, Peoples R China.
发表日期	2021
ISSN	0196-8904
EISSN	1879-2227
卷号	243
英文摘要	Accurate wind speed forecasting and effective wind energy conversion can reduce the operating cost of wind farms. However, many previous studies have been restricted to analyses of wind speed forecasting and wind energy conversion, which may result in poor decisions and inaccurate power scheduling for wind farms. This study develops a wind energy decision system based on forecasting and simulation, which includes two modules: wind speed forecasting and wind energy conversion. In the wind speed forecasting module, an effective secondary denoising strategy based on singular spectrum analysis and ensemble empirical mode decomposition was used to eliminate chaotic noise and extract important features from the original data. Then, a model selection called weighted information criterion was applied to select optimal sub-models for the combined model. To improve the forecasting performance of the combined model, a modified multi-objective grey wolf optimisation algorithm was adopted to optimise the parameters of the sub-models and the weight of the combined model. In the wind energy conversion module, a wind energy conversion curve was established by simulating historical electrical energy data and wind speed data, which can effectively analyse the power generation at each site. The numerical results show that compared with the mean absolute percentage error values of the single models, that of the combined model is reduced by up to 35.57%. Moreover, the standard deviation of the absolute percentage error is decreased by up to 49.88% for wind speed forecasting, and the R2 of the wind energy conversion curve is more than 0.9. Therefore, the proposed combined method can serve as an effective tool for wind farm management and decision-making.
关键词	EMPIRICAL MODE DECOMPOSITION TIME-SERIES REGRESSION ENSEMBLE SPECTRUM
英文关键词	Combined forecasting model; Model selection; Multi-objective algorithm; Wind energy conversion
语种	英语
WOS研究方向	Thermodynamics ; Energy & Fuels ; Mechanics
WOS类目	Thermodynamics ; Energy & Fuels ; Mechanics
WOS记录号	WOS:000685054400003
来源期刊	ENERGY CONVERSION AND MANAGEMENT
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/254959
作者单位	[Wang, Chen] Sun Yat Sen Univ, Sch Intelligent Syst Engn, Shenzhen 518107, Guangdong, Peoples R China; [Zhang, Shenghui] Univ Macau, Dept Comp & Informat Sci Org, State Key Lab Internet Things Smart City, Macau, Peoples R China; [Xiao, Ling] Chongqing Univ Posts & Telecommun, Sch Econ & Management, Chongqing 400065, 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	Wang, Chen,Zhang, Shenghui,Xiao, Ling,et al. Wind speed forecasting based on multi-objective grey wolf optimisation algorithm, weighted information criterion, and wind energy conversion system: A case study in Eastern China[J]. 中国科学院西北生态环境资源研究院,2021,243.
APA	Wang, Chen,Zhang, Shenghui,Xiao, Ling,&Fu, Tonglin.(2021).Wind speed forecasting based on multi-objective grey wolf optimisation algorithm, weighted information criterion, and wind energy conversion system: A case study in Eastern China.ENERGY CONVERSION AND MANAGEMENT,243.
MLA	Wang, Chen,et al."Wind speed forecasting based on multi-objective grey wolf optimisation algorithm, weighted information criterion, and wind energy conversion system: A case study in Eastern China".ENERGY CONVERSION AND MANAGEMENT 243(2021).