气候变化领域集成服务门户(CCPortal): Short-term wind speed time series forecasting based on a hybrid method with multiple objective optimization for non-convex target

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DOI	10.1016/j.energy.2020.119180
	Short-term wind speed time series forecasting based on a hybrid method with multiple objective optimization for non-convex target
	Dong, Yunxuan; Wang, Jing; Xiao, Ling; Fu, Tonglin
通讯作者	Xiao, L (通讯作者)，Chongqing Univ Posts & Telecommun, Sch Econ & Management, Chongqing 400065, Peoples R China.
发表日期	2021
ISSN	0360-5442
EISSN	1873-6785
卷号	215
英文摘要	Accurate and reliable wind speed forecasting (WSF) is crucial for wind power systems. As one of the effective forecast methods, machine learning (ML) methods are employed for wind speed time series forecasting because the excellent ability in fitting the relationship between data and cost function. However, the cost functions with non-convexity make the whole problem poor interpretability and poor robustness. In this paper, a novel hybrid supervised approach is proposed to solve the above problems. The proposed approach has adopted local convolutional neural networks (LCNNs) for convexity preserving of the cost function, in this way, a non-convex problem can be transformed as a convex problem so that heuristic optimization algorithms is adopted to find optimal parameters, and it helps to construct a more stable model. Highway Gate (HG) algorithm is adopted to decrease the computation complexity of the proposed model. The numerical simulation results indicate that the proposed method is not only effective for solving convergence problem cost by non-convexity, but also beneficial to improve accuracy and stability of the traditional ML for wind speed time series forecasting. (C) 2020 Elsevier Ltd. All rights reserved.
关键词	ENERGY MANAGEMENT NEURAL-NETWORK COMBINATION ALGORITHMS
英文关键词	Wind speed forecasting; Convolutional neural networks; Hybrid forecast approach; Optimization algorithm
语种	英语
WOS研究方向	Thermodynamics ; Energy & Fuels
WOS类目	Thermodynamics ; Energy & Fuels
WOS记录号	WOS:000596834000005
来源期刊	ENERGY
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/254595
作者单位	[Dong, Yunxuan] Univ Macau, Dept Elect & Comp Engn, Macau, Peoples R China; [Wang, Jing] Lanzhou Univ Technol, Sch Law, Lanzhou 730050, Gansu, 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, Gansu, Peoples R China; [Fu, Tonglin] Chinese Acad Sci, Shapotou Desert Res & Expt Stn, Northwest Inst Ecoenvironm & Resources, 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	Dong, Yunxuan,Wang, Jing,Xiao, Ling,et al. Short-term wind speed time series forecasting based on a hybrid method with multiple objective optimization for non-convex target[J]. 中国科学院西北生态环境资源研究院,2021,215.
APA	Dong, Yunxuan,Wang, Jing,Xiao, Ling,&Fu, Tonglin.(2021).Short-term wind speed time series forecasting based on a hybrid method with multiple objective optimization for non-convex target.ENERGY,215.
MLA	Dong, Yunxuan,et al."Short-term wind speed time series forecasting based on a hybrid method with multiple objective optimization for non-convex target".ENERGY 215(2021).