Wind Turbine Health Information Mining Based on SCADA Data

The working status of wind turbine can be obtained and fault warning can be given accurately, if the data information mining is efficient. However the existing SCADA data monitoring methods do not take the history and trend into account. A data information mining method based on LSSVR for wind turbine SCADA data is presented in this paper. First, LSSVR model of wind turbine with output power as output and other 30 parameters as input is built by using the SCADA data of wind turbine normal condition. Then, using the LSSVR model, the residual of output power prediction and actual value is obtained. At last, by analyzing the current information, historical information and trend information mined from the residual, wind turbine working status is concluded and early warning is given if necessary. Through cases of both chronic fault and acute fault, the accuracy and effectiveness of the proposed method is verified which means the maintenance cost of WT could be reduced by using the proposed method.