Abstract

The theoretical system of existing civil engineering typhoon models is too simplified and the simulation accuracy is very low. Therefore, in this work a meso-scale weather forecast model (WRF) based on the non-static Euler equation model was introduced to simulate typhoon “Nuri” with high spatial and temporal resolution, focusing on the comparison of wind direction and wind intensity characteristics before, during and after the landing of the typhoon. Moreover, the effectiveness of the meso-scale typhoon “Nuri” simulation was verified by a comparison between the track of the typhoon center based on minimum sea level pressure and the measured track. In this paper, the aerodynamic performance of large wind turbines under typhoon loads is studied using WRF and CFD nesting technology. A 5 MW wind turbine located in a wind power plant on the southeast coast of China has been chosen as the research object. The average and fluctuating wind pressure distributions as well as airflow around the tower body and eddy distribution on blade and tower surface were compared. A dynamic and time-historical analysis of wind-induced responses under different stop positions was implemented by considering the finite element complete transient method. The influence of the stop position on the wind-induced responses and wind fluttering factor of the system were analyzed. Finally, under a typhoon process, the most unfavorable stop position of the large wind turbine was concluded. The results demonstrated that the internal force and wind fluttering factor of the tower body increased significantly under the typhoon effect. The wind-induced response of the blade closest to the tower body was affected mostly. The wind fluttering factor of this blade was increased by 35%. It was concluded from the analysis that the large wind turbine was stopped during the typhoon. The most unfavorable stop position was at the complete overlapping of the lower blade and the tower body (Condition 1). The safety redundancy reached the maximum when the upper blade overlapped with the tower body completely (Condition 5). Therefore, it is suggested that during typhoons the blade of the wind turbine be rotated to Condition 5.

Highlights

  • The microturbulence structure of meso-scale typhoons shows significant differences with that of normal winds

  • In order to systematically study the aerodynamic performance and wind effect characteristics of large-scale wind turbine systems under the typhoon process, a meso-scale weather forecast model (WRF) model based on fluid dynamics and thermodynamics was introduced to simulate typhoon “Nuri” with high spatial and temporal

  • The aerodynamic performance of a large wind turbine under typhoon loads wasstudied by WRF and CFD nesting technology

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Summary

Introduction

The microturbulence structure of meso-scale typhoons shows significant differences with that of normal winds. For studies about the aerodynamic performance of wind turbines under different stop positions, Ke et al [20,21,22,23,24] carried out a series of studies based on large eddy simulation (LES) and finite element technology, mainly covering flow field effect, wind pressure distribution, wind-induced response and wind-induced stability under normal wind conditions. In order to systematically study the aerodynamic performance and wind effect characteristics of large-scale wind turbine systems under the typhoon process, a meso-scale WRF model based on fluid. In order to systematically study the aerodynamic performance and wind effect characteristics of large-scale wind turbine systems under the typhoon process, a meso-scale WRF model based on fluid dynamics and thermodynamics was introduced to simulate typhoon “Nuri” with high spatial and temporal. The most unfavorable stop position for the large wind turbine during the typhoon was revealed

WRF Mode Meshing
Selection of the Parameterization Scheme
Validity Verification and Results Analysis
Verification and Results
Figures to and
Brief to the Windthe
Computational Domain and Meshing
Micro-Scale
Boundary Conditions and Parameter Setting
Average Wind Pressure Coefficient
Coefficient
16. Distribution
Characteristics
Vorticity
Finite Element
Responses
The value was close to
25. The results demonstrated that:
The was by under the the tip tip of Blade
Wind Fluttering Factor
Conclusions
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