Pitch Angle Control Based on Renforcement Learning
According to the random characteristics of external wind speed, time-varying of the internal unit parameters and nonlinearity of wind turbine system, a pitch angle control strategy based on reinforcement learning algorithm for wind turbine is proposed in this paper. The framework of Actor-Critic is adopted in this algorithm and RBF neural network is used to process continuous input and output space. With this algorithm the system can optimize its control parameter in time varying environment. The simulation results of wind power generation system show that the algorithm can quickly converge to the optimal value and has a good dynamic response and strong anti-disturbance.
wind turbine system pitch angle control reinforcement learning
Qin Bin Li Pengcheng Wang Xin Zhu Wanli
Academy of Electric & Information Engineering, Hunan University of Technology, Zhuzhou, Hunan 412007,China
国际会议
长沙
英文
18-21
2014-05-31（万方平台首次上网日期，不代表论文的发表时间）