基于BPNN-PID的风电机组桨距控制分析

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 of wind power generation unit based on BPNN-PID algorithm

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 conducted under matlab/simulink environment.The simulation of 1.5MW wind turbine verified the effectiveness of BPNN-PID algorithm which not only solved the difficulty in parameter tuning of conventional PID controller but also improved the optimization efficiency and achieved excellent control performance.