摘要
主动尾流控制技术通过协调风电场中每台风力机的运行状态,降低上游机组尾流对下游机组的负面影响,进而提高整场发电功率。为探究尾流控制的规律,以10台串列排布的风力机为研究对象,采用Jensen尾流模型与平方和叠加模型计算尾流速度分布,通过鲸鱼优化算法(whale optimization algorithm,WOA)优化风力机的轴向诱导因子分布,并与粒子群优化算法(particle swarm optimization algorithm,PSO)对比。研究结果显示:WOA优化效果更好,收敛速度更快,使风电场输出功率提高了5.63%~42.76%;轴向诱导因子的分布规律和风电场输出功率的优化效果受入流风速影响较小,受风力机的数量及流向间距影响较大。
Active wake control technology mitigates the adverse effects of upstream turbine wakes on downstream turbines by coordinating the operational status of each turbine in a wind farm,thereby enhancing the power generation.To explore the patterns of wake control,10 wind turbines in tandem are taken as the research object.The Jensen wake model and square summation superposition model are used to calculate the wake velocity distribution,and whale optimization algorithm(WOA)is used as the optimization method for axial induction factor distribution whose results are compared with those of particle swarm optimization algorithm(PSO).The results show that the WOA performs better and converges faster than PSO,resulting in a 5.63%to 42.76%increase in the wind farm power output.The distribution pattern of axial induction factors and the optimization effect on wind farm output power are minimally affected by inflow wind speed but are significantly influenced by the number of turbines and their streamwise spacing.
作者
刘一格
赵振宙
马远卓
凌子焱
刘惠文
刘岩
罗乔
LIU Yige;ZHAO Zhenzhou;MA Yuanzhuo;LING Ziyan;LIU Huiwen;LIU Yan;LUO Qiao(College of Energy and Electrical Engineering,Hohai University,Nanjing 211100,Jiangsu Province,China;Institute of Ocean and Offshore Engineering,Hohai University,Nantong 226004,Jiangsu Province,China;Jiangsu Wind Power Engineering Technology Center,Nanjing Vocational University of Industry Technology,Nanjing 210023,Jiangsu Province,China)
出处
《中国电机工程学报》
EI
CSCD
北大核心
2024年第9期3702-3709,I0031,共9页
Proceedings of the CSEE
基金
国家自然科学基金项目(51876054)
江苏风力发电工程技术中心开放基金(ZK22-03-01)
南通市科技项目(JC2021108)。
关键词
风力机
主动尾流控制
尾流模型
鲸鱼优化算法
wind turbine
active wake control
wake model
whale optimization algorithm
