Abstract:

Abstract:It has important significance for realtime monitoring of wind turbine anemometer due to its high failure probability.This paper proposed an anemometer monitoring method based on adjacent wind turbines correlation model for the high correlation of operation conditions and measured values of anemometers among adjacent wind turbines.This paper processed the normal measured data of anemometers of adjacent wind turbines using particle swarm optimization (PSO) algorithm and built a correlation model.In this model,the realtime measured wind velocities of anemometers are considered as the inputs.When a certain wind turbine anemometer is abnormal,the correlation among adjacent wind turbines is destroyed and the predicted residual of the certain wind turbine anemometer will increase significantly,which indicates that anemometer may have a fault. Hence this method could realize the realtime monitoring of anemometer.The practical operation data of a certain wind farm verified the effectiveness of this method.

Key words: Keywords:wind turbine, anemometer;correlation model, condition monitoring, particle swarm optimization algorithm;back propagation neural network, residual