IMECH-IR  > 流固耦合系统力学重点实验室
Wind velocity distribution reconstruction using CFD database with Tucker decomposition and sensor measurement
Qin L; Liu S; Kang Y; Yan SA; Schlaberg HI; Wang Z(王展)
Source PublicationENERGY
2019-01-15
Volume167Pages:1236-1250
ISSN0360-5442
AbstractWind forecasting holds the key to the management of wind power. Previous vector or matrix wind forecast methods may not best reflect the intrinsic inter relationship among the wind velocity components of a three-dimensional wind field. Alternatively, a tensor-based model is developed to reconstruct the wind velocity distribution within a short period of time, enabling a new way for wind forecasting. A third-order CFD database is established by CFD simulations and the Tucker decomposition is used to obtain the tensor basis off site. Then in real time, the tensor basis can be employed to rapidly reconstruct wind velocity distributions in any direction, which can also form a new way to reconstruct wind velocity distribution in 3-D spaces. A comparison of the maximum and relative reconstruction errors shows that the newly proposed method performs better than the authors' previously published wind field reconstruction method. The influences of sampling rate, noise level and sensor distributions on the reconstruction error are also discussed in this paper. Finally, a wind tunnel experiment is carried out to evaluate the accuracy of the proposed method, and in most cases, the experimental results show that relative errors drop around 0.03%-0.4% and maximum errors drop around 0.02%-1.7% when using the newly proposed method. (C) 2018 Elsevier Ltd. All rights reserved.
KeywordWind velocity distribution Third-order CFD database Tucker decomposition Sensor measurement
DOI10.1016/j.energy.2018.11.013
Indexed BySCI ; EI
Language英语
WOS IDWOS:000456351800103
WOS KeywordNUMERICAL WEATHER PREDICTIONS
WOS Research AreaThermodynamics ; Energy & Fuels
WOS SubjectThermodynamics ; Energy & Fuels
Funding OrganizationNSFC [61571189, 61871181] ; State Administration of Foreign Experts Affairs [B13009]
Classification一类
Ranking5+
Citation statistics
Document Type期刊论文
Identifierhttp://dspace.imech.ac.cn/handle/311007/78250
Collection流固耦合系统力学重点实验室
Affiliation1.North China Elect Power Univ, Sch Energy Power & Mech Engn, Beijing 102206, Peoples R China
2.Chinese Acad Sci, Inst Mech, Key Lab Mech Fluid Solid Coupling Syst, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Qin L,Liu S,Kang Y,et al. Wind velocity distribution reconstruction using CFD database with Tucker decomposition and sensor measurement[J]. ENERGY,2019,167:1236-1250.
APA Qin L,Liu S,Kang Y,Yan SA,Schlaberg HI,&王展.(2019).Wind velocity distribution reconstruction using CFD database with Tucker decomposition and sensor measurement.ENERGY,167,1236-1250.
MLA Qin L,et al."Wind velocity distribution reconstruction using CFD database with Tucker decomposition and sensor measurement".ENERGY 167(2019):1236-1250.
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