NARX-Network Based Wind Speed Estimation for Wind Turbines

Abstract

This paper proposes a new wind speed estimation method for the control systems of wind turbines. The nonlinear autoregressive network with exogenous inputs (NARX) is applied to model the wind turbine and estimate the wind speed. The actual data from a wind farm is used to train both the traditional multilayer perceptron neural network (MLP) and the NARX-network. The experimental results show that NARX-network can produce a more accurate estimation than the traditional multilayer perceptron.