基于“应变-载荷”模型的大型风电机组叶片载荷识别研究
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摘要
为了解决风电机组运行过程中叶片载荷在线识别的难题,提出一种基于叶根应变测量的风电机组叶片载荷识别方法。开展叶片属性参数对应变单因素影响分析,基于此设计多因素联合影响正交试验,并利用回归分析来获取叶片属性参数与应变之间的关系模型。在回归分析过程中采用"显著性"判定进一步得到回归修正方程。充分考虑多重载荷的影响建立叶根应变与叶片载荷之间的关系模型。以某43 m长风电叶片为例构建出风电机组三维实体模型,利用CFD和ANASYS数值仿真软件对叶片上分布载荷和叶根应变进行分析。然后,将模型计算结果与有限元仿真结果进行对比分析,佐证所提出"应变-载荷"模型的可行性。
In order to solve the problem of on-line identification of blade load during the operation of wind turbines,a load identification method based on blade root stress measurement is proposed. The influence of single blade property parameters on blade root stress is analysed. Based on this,the orthogonal experiment of joint influence of multiple factors is designed. Then,regression analysis is used to obtain the relationship model between blade property parameters and stress. In the process of regression analysis,the regression correction equation is obtained by using the criterion of"significance". Subsequently,the relationship between blade root stress and blade load is established with a full consideration of multiple load. As an example,a three-dimensional solid model of a wind turbine with 43 meter long blade is constructed. Moreover,the distributed load and root stress on the blade are analysed by employing CFD and ANASYS software. After that,the results of model calculation and finite element simulation are compared and analysed,which proves the feasibility of the "stress-load" model proposed.
In order to solve the problem of on-line identification of blade load during the operation of wind turbines,a load identification method based on blade root stress measurement is proposed. The influence of single blade property parameters on blade root stress is analysed. Based on this,the orthogonal experiment of joint influence of multiple factors is designed. Then,regression analysis is used to obtain the relationship model between blade property parameters and stress. In the process of regression analysis,the regression correction equation is obtained by using the criterion of"significance". Subsequently,the relationship between blade root stress and blade load is established with a full consideration of multiple load. As an example,a three-dimensional solid model of a wind turbine with 43 meter long blade is constructed. Moreover,the distributed load and root stress on the blade are analysed by employing CFD and ANASYS software. After that,the results of model calculation and finite element simulation are compared and analysed,which proves the feasibility of the "stress-load" model proposed.
引文
[1] Sagbansua L, Balo F. Decision making model development in increasing wind farm energy efficiency[J]. Renewable Energy,2017,109:354—362.
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[5]戴巨川.叶片断裂事故条件下直驱式风电机组动态特性分析[J].机械工程学报,2013,49(2):190—198.[5] Dai Juchuan. Dynamic characteristics analyses of large scale directly-driven wind turbines under blade fracture accident condition[J]. Journal of Mechanical Engineerging,2013,49(2):190—198.
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[7] Fernandez G,Usabiaga H,Vandepitte D. An efficient procedure for the calculation of the stress distribution in a wind turbine blade under aerodynamic loads[J].Journal of Wind Engineering and Industrial Aerodynamics,2018,172:42—54.
[8]白叶飞,汪建文,赵元星,等.风力机叶片叶根应力集中区应力状态实验研究[J].太阳能学报,2017,38(12):3406—3411.[8] Bai Yefei, Wang Jianwen, Zhao Yuanxing, et al.Experimental study of stress state in stress concentration area of wind turbine blade root[J]. Acta Energiae Solaris Sinica,2017,38(12):3406—3411.
[9] Schubel P J,Crossley R J,Boateng E K G,et al.Review of structural health and cure monitoring techniques for large wind turbine blades[J]. Renewable Energy,2013,51:113—123.
[10] Lee J-K,Park J-Y,Oh K-Y,et al. Transformation algorithm of wind turbine blade moment signals for blade condition monitoring[J]. Renewable Energy,2015,79:209—218.
[11] Dimitrov N, Bitsche R D, Blasques J P. Spatial reliability analysis of a wind turbine blade cross section subjected to multi-axial extreme loading[J]. Structural Safety,2017,66:27—37.
[2] Kaldellis J K,Apostolou D. Life cycle energy and carbon footprint of offshore wind energy. Comparison with onshore counterpart[J]. Renewable Energy,2017,108:72—84.
[3] Schallenberg-Rodríguez J,Montesdeoca N G. Spatial planning to estimate the offshore wind energy potential in coastal regions and islands. Practical case:The Canary Islands[J]. Energy,2018,143:91—103.
[4] Kim B,Kim W,Bae S,et al. Aerodynamic design and performance analysis of multi-MW class wind turbine blade[J]. Journal of Mechanical Science and Technology,2011,25(8):1995.
[5]戴巨川.叶片断裂事故条件下直驱式风电机组动态特性分析[J].机械工程学报,2013,49(2):190—198.[5] Dai Juchuan. Dynamic characteristics analyses of large scale directly-driven wind turbines under blade fracture accident condition[J]. Journal of Mechanical Engineerging,2013,49(2):190—198.
[6] Dai J C,Hu Y P,Liu D S,et al. Aerodynamic loads calculation and analysis for large scale wind turbine based on combining bem modified theory with dynamic stall model[J]. Renewable Energy, 2011, 36(3):1095—1104.
[7] Fernandez G,Usabiaga H,Vandepitte D. An efficient procedure for the calculation of the stress distribution in a wind turbine blade under aerodynamic loads[J].Journal of Wind Engineering and Industrial Aerodynamics,2018,172:42—54.
[8]白叶飞,汪建文,赵元星,等.风力机叶片叶根应力集中区应力状态实验研究[J].太阳能学报,2017,38(12):3406—3411.[8] Bai Yefei, Wang Jianwen, Zhao Yuanxing, et al.Experimental study of stress state in stress concentration area of wind turbine blade root[J]. Acta Energiae Solaris Sinica,2017,38(12):3406—3411.
[9] Schubel P J,Crossley R J,Boateng E K G,et al.Review of structural health and cure monitoring techniques for large wind turbine blades[J]. Renewable Energy,2013,51:113—123.
[10] Lee J-K,Park J-Y,Oh K-Y,et al. Transformation algorithm of wind turbine blade moment signals for blade condition monitoring[J]. Renewable Energy,2015,79:209—218.
[11] Dimitrov N, Bitsche R D, Blasques J P. Spatial reliability analysis of a wind turbine blade cross section subjected to multi-axial extreme loading[J]. Structural Safety,2017,66:27—37.