Wind speed estimation based control of Stand-Alone DOIG for wind energy conversion system

Abstract

A sensor less wind speed estimation scheme for variable-speed wind turbine generators has been analysed in this paper. Neural network principles are applied for sensor less wind speed estimation. Model of one pitch controlled horizontal axis wind turbine along with DOIG based generation system has been used for this study. The aerodynamic characteristics of the wind turbine are approximated by a radial basis function network based nonlinear input-output mapping. Based on this mapping, the wind speed is estimated from the measured turbine mechanical power, turbine angular speed and pitch angle. The resulting WTG system efficiently and reliably estimates the wind speed without any mechanical anemometers.