Common virtual wind speed sensors for wind farm based on finite impulse response neural network

Abstract

Wind speed sensors of wind turbines has high fault rate,those faults may lead wind turbines into safety risks and energy production loss.However,many current methods of improving reliability of wind speed information face the challenges of high cost or high error.A virtual wind speed sensor based on spatial correlation was presented in this paper.Its key character is generating a downwind turbine's logic wind speed based on a special upwind turbine's real wind speed.The calculation mode of logic wind speed just need the outputs of the existed wind speed and direction sensors.A FIR(Finite Impulse Response) neural network computing model was proposed for deal with the complexity of logic wind speed calculating.Moreover,key technologies were discussed for building the virtual wind speed sensor system.The logic wind speed generated by virtual sensor can be used for providing reliable wind speed information input to a turbine controller.The approach presented in this paper is applicable to wind turbines of any type in wind farms.