Novel strategy for fault e-diagnosis of wind energy conversion systems using wavelet analysis based on Rt-Lab and Arduino

The diagnosis of wind energy conversion systems (WECS) turns out to be necessary because their relatively high cost operation and maintenance. Wind turbines are hard-to-access structures, they often located in remote areas. Therefore, a (e-diagnosis) is required. This paper proposes an alternative approach for the e-diagnosis WECS based on discrete wavelet transform (DWT) frequency analysis aero generator stator currents. To validate this approach, real-time hardware loop (HIL) used simulate mathematical model induction OPAL-RT OP5600 platform generate currents rotor speed. DWT applied current signal, which has huge number points that not supported direct transmission by Arduino Mega RobotDyn its limited sample time. absolute values peak (MDWT) sent as point’s packages form station via ESP8266 integrated Wi-Fi board monitor SCIG states determine broken bars.