Uncertainty Quantification of a Coupled Model for Wind Prediction at a Wind Farm in Japan

Jonghoon Jin, Yuzhang Che, Jiafeng Zheng and Feng Xiao
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Jonghoon Jin: Department of Mechanical Engineering, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo 152-8550, Japan
Yuzhang Che: Department of Mechanical Engineering, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo 152-8550, Japan
Jiafeng Zheng: College of Atmospheric Science, Chengdu University of Information Technology, Chengdu 610225, China
Feng Xiao: Department of Mechanical Engineering, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo 152-8550, Japan

Energies, 2019, vol. 12, issue 8, 1-18

Abstract: Reliable and accurate short-term prediction of wind speed at hub height is very important to optimize the integration of wind energy into existing electrical systems. To this end, a coupled model based on the Weather Research Forecasting (WRF) model and Open Source Field Operation and Manipulation (OpenFOAM) Computational Fluid Dynamics (CFD) model is proposed to improve the forecast of the wind fields over complex terrain regions. The proposed model has been validated with the quality-controlled observations of 15 turbine sites in a target wind farm in Japan. The numerical results show that the coupled model provides more precise forecasts compared to the WRF alone forecasts, with the overall improvements of 26%, 22% and 4% in mean error (ME), root mean square error (RMSE) and correlation coefficient (CC), respectively. As the first step to explore further improvement of the coupled system, the polynomial chaos expansion (PCE) approach is adopted to quantitatively evaluate the effects of several parameters in the coupled model. The statistics from the uncertainty quantification results show that the uncertainty in the inflow boundary conditions to the CFD model affects more dominantly the hub-height wind prediction in comparison with other parameters in the turbulence model, which suggests an effective approach to parameterize and assimilate the coupling interface of the model.

Keywords: uncertainty quantification; coupled model; wind forecasting; WRF model; OpenFOAM (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: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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