A NBM based on P-N relationship for DFIG wind turbine fault detection

Abstract

Supervisory control and data acquisition (SCADA) data has been widely applied to identify abnormal conditions in wind turbine generators (WTG). One approach was to apply Artificial Intelligence (AI) to SCADA data, comparing the predicted power output of a WTG and its actual output and using the prediction error as an indicator to detect faults. However, complicated training processes limit its application. This paper presents a normal behavior model (NBM), based on power output-generator speed (P-N) curve, to analyze SCADA data from modern pitch regulated WTGs for detecting anomalies. Through analysis of the operational characteristics of the pitch regulated WTG, it is found that inaccuracies in wind speed measurement, the inertia of the rotor, yaw and pitch misalignments, and air density fluctuation may affect the performance of the power curve monitoring algorithms. This paper shows that under normal conditions the P-N curve based NBM performs better when fitting the SCADA data to WTG output under normal conditions than the power curve. Results demonstrate that it can give alarm to forthcoming faults earlier than the existing condition monitoring system (CMS).

Detection and classification of faults in pitch-regulated wind turbine generators using normal behaviour models based on performance curves

“…The data in the red rectangle illustrates that the generator may still rotate when wind speed is lower than v r . When the wind speed reduces to the cut-in wind speed and further reduces, the change in the generator speed lags the wind speed due to the inertia of the rotor [19]. The red circled data demonstrates a similar relationship, i.e.…”

“…In Fig. 3, the measured data circled by the red dashed rectangle shows that there is positive power output when the measured wind speed is lower than the cut-in wind speed (4 m/s) due to the rotor inertia and constant speed control in grid connection state [19]. When the wind speed reduces to around v cut-in , for short periods of time the generator speed maintains at n GCS , and the GC state is maintained.…”

“…However, as demonstrated above using real world data, these measured values have a large spread over the theoretical curves, due to the practical reaction times of the various system components. As discussed in [19], they cannot be relied on to model the theoretical relationship between the measurements and wind speed due to the rotor inertia.…”

“…Any deviations from the envelopes indicate a WTG pitching faults. Any pitch controller malfunction and slip ring pollution, critical failure modes of WTGs, results in that the pitch angle does not meet expectations and causes wind power extraction to differ from normal operational conditions [19].…”