基于尾流风速场风速矢量计算的风电场输出功率优化模型
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摘要
针对尾流效应在风电机组之间产生影响的问题,为了更加合理利用风能,增加风场的输出功率,在风场面积不变的前提下对风场内风电机组进行布局优化,根据风场实际仿真数据训练建立尾流风速场风速矢量计算模型和尾流影响区域风速计算误差函数,迭代计算尾流区域的风速矢量最优解;然后,基于改进粒子群算法对粒子群进行参数密度熵分簇优化,对不同种群进行寻优,计算出最优的风场布局排列,提高计算机的计算效率;最后,通过CFD生变化时,模型能够计算出尾流效应区域的风速矢量,仿真结果及分析证明模型和优化算法的正确性。
For the problem that the wake effect has an influence between the wind turbines,in order to make more rational use of the wind power and increase the output of the wind farm,the optimization method of the layout of wind turbines in the wind farm under the premise of constant wind farm area is proposed. Firstly,according to the actual simulation data of wind field,the wind speed vector calculation model of wake wind speed field and the wind speed calculation error function of wake area are established. The wind speed vector optimal solution of wake region is iteratively calculated. Then,based on the improved particle swarm optimization algorithm,the particle swarm is optimized by optimized parameter density entropy clusters and different populations. The optimal wind field layout is calculated and the computational efficiency of the computer is improved. Finally,this paper simulates the wake velocity vector iteration model and the wind turbine layout calculated by the improved particle swarm optimization algorithm through CFD simulation. When the input wind speed vector changes,the model can calculate the wind speed vector of the wake effect region. The simulation results and analysis prove the correctness of the model and the optimization algorithm.
For the problem that the wake effect has an influence between the wind turbines,in order to make more rational use of the wind power and increase the output of the wind farm,the optimization method of the layout of wind turbines in the wind farm under the premise of constant wind farm area is proposed. Firstly,according to the actual simulation data of wind field,the wind speed vector calculation model of wake wind speed field and the wind speed calculation error function of wake area are established. The wind speed vector optimal solution of wake region is iteratively calculated. Then,based on the improved particle swarm optimization algorithm,the particle swarm is optimized by optimized parameter density entropy clusters and different populations. The optimal wind field layout is calculated and the computational efficiency of the computer is improved. Finally,this paper simulates the wake velocity vector iteration model and the wind turbine layout calculated by the improved particle swarm optimization algorithm through CFD simulation. When the input wind speed vector changes,the model can calculate the wind speed vector of the wake effect region. The simulation results and analysis prove the correctness of the model and the optimization algorithm.
引文
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[13]刘小民,赵嘉,李典.单圆弧等厚叶片前后缘多元藕合仿生设计及降噪机理研究[J].西安交通大学学报,2015,39(3):1-10.[13]Liu Xiaomin,Zhao Jia,Li Dian.Multi-discrepancy bionic design and noise reduction mechanism for the front and rear edge of a single circular-arc thick blade[J].Journal of Xi’an Jiaotong University,2015,39(3):1-10.
[14]褚双磊.用于轴流风机的轴流叶轮气动性能试验研究[J].流体机械,2014,42(4):6-10.[14]Chu Shuanglei.Experimental research on the axial-flow impeller aerodynamic performance of the axial-flow fan[J].Fluid Machinery,2014,42(4):6-10.
[2]郭辉,岳良明,王海文.大型水平轴风力机风轮模型风洞试验[J].太阳能学报,2018,39(1):253-257.[2]Guo Hui,Yue Liangming,Wang Haiwen.Wind tunnel test for rotor model of a large scale horizontal-axis wind turbine[J].Acta Engergiae Solaris Sinica,2018,39(1):253-257.
[3]Wilson J M,Davis C J,Venayagamoorthy S K,et al.Comparisons of horizontal-axis wind turbine interaction models[J].Journal of Solar Energy Engineering,2015,137(3):031001-1-031001-8.
[4]张兆德,张鑫文,徐超.大型风力机叶片气动噪声研究一种有效的支持向量机参数优化算法[J].太阳能学报,2017,38(5):1346-1353.[4]Zhang Zhaode,Zhang Xinwen,Xu Chao.Study of aerodynamic noise for large-scale wind turbine[J].Acta Energiae Solaris Sinica,2017,38(5):1346-1353.
[5]李春曦,李新颖.叶片切割对轴流风机性能影响的数值研究[J].机械工程学报,2014,50(10):183-190.[5]Li Chunxi,Li Xinying.Numerical study on the effect of blade cutting on axial fan performance[J].Chinese Journal of Mechanical Engineering,2014,50(10):183-190.
[6]刘洋,吴国庆,宋晨光.1 kW垂直轴风力发电机叶片静力分析[J].南通大学学报:自然科学版,2016,15(3):1-6.[6]Liu Yang,Wu Guoqing,Song Chenguang.Static force analysis of 1 kW vertical axis wind turbine blades[J].Journal of Nantong University:Natural Science Edition,2016,15(3):1-6.
[7]Bartl J,Pierella F,Sxtrana L.Wake measurements behind an array of two model wind turbines[J].Energy Procedia,2012,24:305-312.
[8]李彩林,郭宝云,季铮.多视角三维激光点云全局优化整体配准算法[J].测绘学报,2015,44(2):183-189.[8]Li Cailin,Guo Baoyun,Ji Zheng.Globally optimized global registration algorithm for multi-view 3D laser point cloud[J].Acta Geodaetica et Cartographic Sinica,2015,44(2):183-189.
[9]Gao Xiaoxia,Yang Hongxing,Lu Lin.Study on offshore wind power potential and wind farm optimization in Hong Kong[J].Applied Energy,2014,130(5):519-531.
[10]Wen Binrong,Wei Sha,Wei Kexiang.Power fluctuation and power loss of wind turbines due to wind shear and tower shadow[J].Frontiers of Mechanical Engineering,2017,12(3):321-332
[11]王慕华,惠建忠,唐千红,等.风电功率预测预报系统的设计与实现[J].计算机与现代化,2013,(7):224-227.[11]Wang Muhua,Hui Jianzhong,Tang Qianhong,et al.Design and implementation of wind power prediction and forecasting system[J].Computer and Modernization,2013,(7):224-227.
[12]文晓庆,柳阳威,方乐,等.提高k-ωSST模型对翼型失速特性的模拟能力[J].北京航空航天大学学报,2013,39(8):1127-1132.[12]Wen Xiaoqing,Liu Yangwei,Fang Le,et al.To improve the simulation capability of the k-ωSST model for airfoil stall characteristics[J].Journal of Beijing University of Aeronautics and Astronautics,2013,39(8):1127-1132.
[13]刘小民,赵嘉,李典.单圆弧等厚叶片前后缘多元藕合仿生设计及降噪机理研究[J].西安交通大学学报,2015,39(3):1-10.[13]Liu Xiaomin,Zhao Jia,Li Dian.Multi-discrepancy bionic design and noise reduction mechanism for the front and rear edge of a single circular-arc thick blade[J].Journal of Xi’an Jiaotong University,2015,39(3):1-10.
[14]褚双磊.用于轴流风机的轴流叶轮气动性能试验研究[J].流体机械,2014,42(4):6-10.[14]Chu Shuanglei.Experimental research on the axial-flow impeller aerodynamic performance of the axial-flow fan[J].Fluid Machinery,2014,42(4):6-10.