A Fast Simulation Method for Wind Turbine Blade Icing Integrating Physical Simulation and Statistical Analysis

Wei Jiang, Renqiang Wen, Ming Qin (), Guohan Zhao, Long Ma, Jun Guo and Jinbo Wu
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Wei Jiang: School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Renqiang Wen: Science and Technology Research Institute (STRI), China Three Gorges Corporation, Beijing 101100, China
Ming Qin: Science and Technology Research Institute (STRI), China Three Gorges Corporation, Beijing 101100, China
Guohan Zhao: China Yangtze Power Co., Ltd., Wuhan 430010, China
Long Ma: China Yangtze Power Co., Ltd., Wuhan 430010, China
Jun Guo: School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Jinbo Wu: Science and Technology Research Institute (STRI), China Three Gorges Corporation, Beijing 101100, China

Energies, 2024, vol. 17, issue 22, 1-17

Abstract: Simulating wind turbine blade icing quickly is important for wind farms to issue early warnings and effectively deal with the adverse effects of cold weather. However, current numerical simulation methods suffer from high computational costs and lack straightforward acceleration techniques for practical ice prediction. Here, we developed a fast and simple blade icing simulation method via an integrated physical simulation and statistical analysis method. This method consists of two steps: firstly, numerical simulation with CFD, and secondly, table look-up calculations. Over 10,000 sets of wind turbine blade icing simulations based on FENSAP-ICE and an NACA64-A17 wing were conducted to develop this method and analyze the influences of environmental factors on blade icing. The results show that ice thickness generally increases with an increase in wind speed, a decrease in temperature, and an increase in liquid water content (LWC), but there is a nonlinear relationship between them. For example, ice thickness has a linear relationship with the LWC within a certain range but hardly changes with a LWC beyond that range. The validation results show that the fast simulation method established in this paper has good consistency with the original numerical simulation method. It can greatly improve the computational efficiency of icing simulations while retaining the accuracy of numerical simulations. It takes less than 1 s to complete over 1000 sets of icing simulations, which offers potential for the fast prediction of wind turbine blade icing in the future.

Keywords: wind turbine; blade icing; FENSAP-ICE; look-up table method; fast numerical simulation technique; environmental factor (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: 2024
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