Estimation of wind turbine rotor power coefficient using RMP model

This paper presents an estimation of the rotor power coefficient (C _p) curve, which is useful for pitch angle control of a wind turbine system. The C_p curve is affected by several factors such as the structure of a wind turbine, surrounding environment in which the wind turbine built, and its method of control, etc. Therefore, it is necessary to estimate this curve in real-time using direct measurements from the generator and wind turbine. To achieve the optimal estimation for the C_p curve, the reduced multivariate polynomial (RMP) model is applied because it can be basically represented in a polynomial form. Unlike general neural network algorithms, the RMP model avoids a training process. This characteristic makes it possible to apply to the real-time estimation in a practical situation. Also, the first-order partial derivatives of the C_p curve are easily computed by using the RMP model. This derivative information can be effectively used to maximize turbine output power by a proper pitch angle control. The simulation results show that the proposed RMP model provides a good estimation performance in a fast and effective manner.