郑州大学学报（工学版）2025，Vol.46Issue(6)：66-74,9.DOI:10.13705/j.issn.1671-6833.2025.03.009
基于数据驱动的风电场等效建模及主动尾流控制
Data-driven Equivalent Modeling and Active Wake Control of a Wind Farm
摘要
Abstract
In order to reduce the influence of wake disturbance on the total output power of wind farm,Informer neural network algorithm was proposed in the proposed wind farm yaw optimization control framework,and an intel-ligent equivalent model of power conversion for wind farm yaw control was established.Based on the present model,an optimization problem maximizing the power output of wind farm with yaw angles as decision variables was de-fined,and particle swarm optimization algorithm was used to obtain the optimal yaw angle of each wind turbine and reduce the wake interference.Firstly,a wind farm consisting of 14 wind turbines was built,and its layout was Pen-manshiel wind farm.Secondly,wind data was used to model the wind farm equivalently,and the results of the In-former model were compared with LSTM,GRU,RNN,and Transformer.The results showed that the established Informer intelligent equivalent model could consist with the actual characteristics of the wind farms.Comparing the proposed algorithm with the mantis search algorithm,the proposed algorithm could increase the total power of wind farms by 1.94 MW with the wind speed of 10 m/s and the wind direction of 195°.With continuous wind conditions(measured wind data on a certain day),the total power of the wind farm was increased by 292.97 kW on average,and the improvement results were superior to the mantis search algorithm.The proposed algorithm could improve the overall output power of the wind farm well.关键词
风电场/尾流效应/Informer神经网络/主动尾流控制/粒子群优化算法Key words
wind farms/wake effect/Informer neural network/active wake control/particle swarm optimization分类
信息技术与安全科学引用本文复制引用
张建华,张梦佳,黄德豪,赵思..基于数据驱动的风电场等效建模及主动尾流控制[J].郑州大学学报（工学版）,2025,46(6):66-74,9.基金项目
国家自然科学基金资助项目(61973116) （61973116）
国家重点研发计划项目(2019YFB1505400) （2019YFB1505400）
