摘要
变桨控制技术是风力发电机组的核心技术之一,开展对风力发电机组变桨控制方面的研究具有重要的理论和应用价值。根据风力发电机组在额定风速以上如何保持输出功率稳定和降低风轮转速波动的控制技术进行研究,在传统的变桨距控制策略基础上,提出了基于BP神经网络(Neural Network,NN)整定PID的控制策略,并在Matlab/simulink环境下对PID控制和BP神经网络控制相结合的复合控制系统进行建模与分析。对1.5MW风电机组的仿真验证了BPNN-PID算法的有效性,提出算法不仅能够解决传统PID控制器参数整定困难的问题,而且优化效率更高,可以得到优良的控制性能。
Variable pitch control technique is one of the core technologies of wind power generation units, and the researches on pitch control of wind turbine generators have important theoretical and practical values. We study the control techniques about how to maintain stable output power and reduce rotor speed＂ fluctuation when the generator unit operates above the rated wind speed. Based on the traditional methods of pitch control, the control strategy to tune PID through BP Neural Network （BPNN） is proposed. Modeling and analysis of the integrated control system combining PID control and BP neural network control are con- ducted under matlab/simulink environment. The simulation of l. 5MW wind turbine verified the effectiveness of BPNN - PID al- gorithm which not only solved the difficulty in parameter tuning of conventional PID controller but also improved the optimization efficiency and achieved excellent control performance.
作者
潘磊
冯浩
王海华
胡煜
PAN Lei FENG Hao WANG Haihua HU Yu(Jiangsu Power Design Institute Co. Ltd. , China Energy Engineering Group, Nanjing 211100)
出处
《人民长江》
北大核心
2017年第9期54-60,共7页
Yangtze River
关键词
BP神经网络
PID
变桨距
转速波动
风力发电系统
BP neural network
PID
variable pitch control
rotor speed fluctuation
wind power generation system
