A Gaussian RBF Network Based Wind Speed Estimation Algorithm for Maximum Power Point Tracking
This paper proposes a Gaussian radial basis function network (GRBFN) based wind speed estimation algorithm for maximum power point tracking (MPPT) of wind power generation system (WPGS).A specific design of the proposed control algorithm for the WPGS with a doubly-fed induction generator (DFIG) is presented.The aerodynamic characteristics of the turbine are approximated by a GRBFN based nonlinear input-output mapping.Based on this nonlinear mapping, the wind speed is estimated from the measured generator electrical output power while taking into account the power losses in system and the dynamic process of shaft system.The estimated wind speed is then used to determine the optimum DFIG rotor speed for maximum wind power extraction.Then the DFIG rotor speed is controlled with the wind speed change, the maximum power extraction can be achieved.Simulation model of 1MW WPGS is built in MATLB/SIMULINK software.The validity and feasibility of the proposed control algorithm is verified by simulation experiment.The simulation results show that the wind speed can be estimated accurately and WPGS can operate in the optimum operating point without mechanical anemometer.
GRBFN wind speed estimation sensorless control DFIG MPPT vector control
Lei Tian Qiang Lu Wen-zhuo Wang
State Grid Electric Power Research Institute,Nanjing,210003 China
国际会议
成都
英文
515-519
2011-09-27（万方平台首次上网日期，不代表论文的发表时间）