SUN Qunli, LIU Changliang, ZHOU Ying. Abnormal detection of operation conditions of wind turbine based on state curve[J]. Thermal power generation, 2019, 48(7): 110-116.
DOI:
SUN Qunli, LIU Changliang, ZHOU Ying. Abnormal detection of operation conditions of wind turbine based on state curve[J]. Thermal power generation, 2019, 48(7): 110-116. DOI: 10.19666/j.rlfd.201901028.
Abnormal detection of operation conditions of wind turbine based on state curve
In order to improve the utilization rate and power generation of wind turbines
and reduce the cost of maintenance and replacement of wind turbines
it is necessary to monitor the operating conditions. In this paper
five state curves of the unit
including the wind speed-power curve
the wind speed-rotor speed curve
the wind speed-pitch angle curve
the rotor speed-power curve
and the rotor speed-pitch angle curve
are introduced theoretically. Then
they are analyzed combining with the actual operational data. The results show that
due to the randomness of wind speed and the inertia of wind turbines
the first three curves does not allow the wind turbine to distinguish normal operation status from a fault status. However
the rotor speed-power curve and rotor speed-pitch angle curve are able to accurately monitor the abnormal conditions of the wind turbine. On the basis of the last two state curves
the distribution of different operating conditions of the unit is analyzed
and corresponding evaluation systems are established for each operating condition. The fault case study indicates that
this method can sense the unit's abnormal situation in advance
and effectively improve the state monitoring accuracy of the system.