Applicability of WorldCover in Wind Power Engineering: Application Research of Coupled Wake Model Based on Practical Project

Jing Zhang, Jixing Chen, Hao Liu, Yining Chen, Jingwen Yang, Zongtao Yuan and Qingan Li
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Jing Zhang: Beijing RETEC New Energy Technology Co., Ltd., Beijing 100079, China
Jixing Chen: Department of Electrical Engineering, School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 100096, China
Hao Liu: CSSC Windpower Development Co., Ltd., Beijing 100097, China
Yining Chen: Department of Atmospheric Science, School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
Jingwen Yang: Beijing RETEC New Energy Technology Co., Ltd., Beijing 100079, China
Zongtao Yuan: Beijing RETEC New Energy Technology Co., Ltd., Beijing 100079, China
Qingan Li: Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China

Energies, 2023, vol. 16, issue 5, 1-16

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.

Keywords: WorldCover; landcover; roughness; roughness length; wake model; Eddy-Viscosity; Deep Array; coupled wake model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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