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Article type: Research Article
Authors: Ma, Junpeng; * | Liu, Feiyan | Xiao, Chenggang | Wang, Kairan | Liu, Zirui
Affiliations: Ningxia Electric Power Engineering Co., Ltd, Yinchuan, Ningxia, China
Correspondence: [*] Correspondence to: Junpeng Ma. E-mail: ju43572167@163.com.
Abstract: The wake effect of wind farm can reduce the incoming wind speed at the wind turbine located in the downstream direction, resulting in the decrease of global output. WRF model adopts a three-layer two-way nested grid division scheme to simulate the upper atmospheric circulation, obtain wind speed, wind direction and other data that can truly reproduce the fluid characteristics of the regional wind farm group. The boundary conditions and solution conditions of CFD model are set, and the computational fluid dynamics model of the region is obtained. WRF is coupled with CFD, and Fitch wake model is introduced into it. By introducing the drag coefficient of wind turbine into the calculation of wind speed and turbulent kinetic energy in CFD-WRF coupling model, the wind field characteristics and wake effect of wind farm are simulated online. Monte Carlo sampling method is used to obtain random wind resource data in CFD-WRF coupling model, and then the sampled data is used to calculate the group output of wind farms, and evaluate the impact of wake effect on wind farm treatment. The experimental results show that this method can effectively analyze the characteristic data of regional wind field, and the calculation time of RANS method is about 3 s. Due to the wake effect, the overall output and efficiency of wind field will be significantly reduced.
Keywords: CFD-WRF coupling, wind resource map, wind farm group, wake effect evaluation, wind speed and direction data, fitch wake model
DOI: 10.3233/JIFS-233273
Journal: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 11425-11437, 2023
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