LAPSE:2023.20264
Published Article

LAPSE:2023.20264
Applicability of WorldCover in Wind Power Engineering: Application Research of Coupled Wake Model Based on Practical Project
March 17, 2023
Abstract
This paper discusses how the incorporation of high-resolution ground coverage dataset ESA WorldCover into a wind flow field and wake simulation calculation, as well as the use of the coupled wake model for wind farm output simulation, can improve the accuracy of wind resource assessment using engineering examples. In the actual case of grid-connected wind farms in central China, SCADA wind speed data is reconstructed to the free flow wind speed in front of the wind turbine impeller using the transfer function of the nacelle, and the wind farm is modeled using OpenWind software, simulating the wind speed at the height of each wind turbine hub and each wind turbine output. The results show that when other initial data are consistent, using ESA’s high-precision land cover dataset WorldCover 10 m to make roughness lengths which improves the wind farm output simulation accuracy by 8.91%, showing that it is worth trying to apply WorldCover 10 m to the wind farm simulation design. At the same time, this case is used to compare and analyze the application of the Eddy-Viscosity wake model and the two coupled wake models based on the Eddy-Viscosity wake model. The results show that the coupled wake model will have higher accuracy than the Deep Array Eddy Viscosity wake model and it is 1.24% more accurate than the Eddy Viscosity wake model, and the ASM Eddy Viscosity wake model is 5.21% more accurate than the Eddy Viscosity wake model.
This paper discusses how the incorporation of high-resolution ground coverage dataset ESA WorldCover into a wind flow field and wake simulation calculation, as well as the use of the coupled wake model for wind farm output simulation, can improve the accuracy of wind resource assessment using engineering examples. In the actual case of grid-connected wind farms in central China, SCADA wind speed data is reconstructed to the free flow wind speed in front of the wind turbine impeller using the transfer function of the nacelle, and the wind farm is modeled using OpenWind software, simulating the wind speed at the height of each wind turbine hub and each wind turbine output. The results show that when other initial data are consistent, using ESA’s high-precision land cover dataset WorldCover 10 m to make roughness lengths which improves the wind farm output simulation accuracy by 8.91%, showing that it is worth trying to apply WorldCover 10 m to the wind farm simulation design. At the same time, this case is used to compare and analyze the application of the Eddy-Viscosity wake model and the two coupled wake models based on the Eddy-Viscosity wake model. The results show that the coupled wake model will have higher accuracy than the Deep Array Eddy Viscosity wake model and it is 1.24% more accurate than the Eddy Viscosity wake model, and the ASM Eddy Viscosity wake model is 5.21% more accurate than the Eddy Viscosity wake model.
Record ID
Keywords
coupled wake model, Deep Array, Eddy-Viscosity, landcover, roughness, roughness length, wake model, WorldCover
Subject
Suggested Citation
Zhang J, Chen J, Liu H, Chen Y, Yang J, Yuan Z, Li Q. Applicability of WorldCover in Wind Power Engineering: Application Research of Coupled Wake Model Based on Practical Project. (2023). LAPSE:2023.20264
Author Affiliations
Zhang J: Beijing RETEC New Energy Technology Co., Ltd., Beijing 100079, China [ORCID]
Chen J: Department of Electrical Engineering, School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 100096, China
Liu H: CSSC Windpower Development Co., Ltd., Beijing 100097, China
Chen Y: Department of Atmospheric Science, School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China [ORCID]
Yang J: Beijing RETEC New Energy Technology Co., Ltd., Beijing 100079, China
Yuan Z: Beijing RETEC New Energy Technology Co., Ltd., Beijing 100079, China
Li Q: Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China
Chen J: Department of Electrical Engineering, School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 100096, China
Liu H: CSSC Windpower Development Co., Ltd., Beijing 100097, China
Chen Y: Department of Atmospheric Science, School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China [ORCID]
Yang J: Beijing RETEC New Energy Technology Co., Ltd., Beijing 100079, China
Yuan Z: Beijing RETEC New Energy Technology Co., Ltd., Beijing 100079, China
Li Q: Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China
Journal Name
Energies
Volume
16
Issue
5
First Page
2193
Year
2023
Publication Date
2023-02-24
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en16052193, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.20264
This Record
External Link

https://doi.org/10.3390/en16052193
Publisher Version
Download
Meta
Record Statistics
Record Views
244
Version History
[v1] (Original Submission)
Mar 17, 2023
Verified by curator on
Mar 17, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.20264
Record Owner
Auto Uploader for LAPSE
Links to Related Works
(0.07 seconds)
[0.07 s]
