A New Fault Diagnosis Algorithm for PMSG Wind Turbine Power Converters under Variable Wind Speed Conditions
School of Energy and Power Engineering, Nanjing University of Science and Technology, No. 200, Xiao Ling Wei, Nanjing 210094, China
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Author to whom correspondence should be addressed.
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These authors contributed equally to this work.
Academic Editor: Frede Blaabjerg
Energies 2016, 9(7), 548; https://doi.org/10.3390/en9070548
Received: 3 May 2016 / Revised: 7 July 2016 / Accepted: 8 July 2016 / Published: 15 July 2016
Although Permanent Magnet Synchronous Generator (PMSG) wind turbines (WTs) mitigate gearbox impacts, they requires high reliability of generators and converters. Statistical analysis shows that the failure rate of direct-drive PMSG wind turbines’ generators and inverters are high. Intelligent fault diagnosis algorithms to detect inverters faults is a premise for the condition monitoring system aimed at improving wind turbines’ reliability and availability. The influences of random wind speed and diversified control strategies lead to challenges for developing intelligent fault diagnosis algorithms for converters. This paper studies open-circuit fault features of wind turbine converters in variable wind speed situations through systematic simulation and experiment. A new fault diagnosis algorithm named Wind Speed Based Normalized Current Trajectory is proposed and used to accurately detect and locate faulted IGBT in the circuit arms. It is compared to direct current monitoring and current vector trajectory pattern approaches. The results show that the proposed method has advantages in the accuracy of fault diagnosis and has superior anti-noise capability in variable wind speed situations. The impact of the control strategy is also identified. Experimental results demonstrate its applicability on practical WT condition monitoring system which is used to improve wind turbine reliability and reduce their maintenance cost.
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Keywords:
PMSG wind turbine; power converter; fault diagnosis; wind speed; turbulence
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MDPI and ACS Style
Qiu, Y.; Jiang, H.; Feng, Y.; Cao, M.; Zhao, Y.; Li, D. A New Fault Diagnosis Algorithm for PMSG Wind Turbine Power Converters under Variable Wind Speed Conditions. Energies 2016, 9, 548.
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