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Durham e-Theses
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Wind Turbine Generator Condition Monitoring
via the Generator Control Loop

ZAGGOUT, MAHMOUD,NOUH (2013) Wind Turbine Generator Condition Monitoring
via the Generator Control Loop.
Doctoral thesis, Durham University.



This thesis focuses on the development of condition monitoring techniques for application in wind turbines, particularly for offshore wind turbine driven doubly fed
induction generators. The work describes the significant development of a physical condition monitoring Test Rig and its MATLAB Simulink model to represent modern variable speed wind turbine and the innovation and application of the rotor side control signals for the generator fault detection. Work has been carried out to develop a physical condition monitoring Test Rig from open loop control, with a wound rotor induction generator, into closed loop control with a doubly fed induction generator. This included designing and building the rotor side converter, installing the back-to-back converter and other new instrumentation. Moreover, the MATLAB Simulink model of the Test Rig has been developed to represent the closed loop control, with more detailed information on the Rig components and instrumentation and has been validated against the physical system in the time and frequency domains. A fault detection technique has been proposed by the author based on frequency analysis of the rotor-side control signals, namely; d-rotor current error, q-rotor current error and q-rotor current, for wind turbine generator fault detection. This technique has been investigated for rotor electrical asymmetry on the physical Test Rig and its MATLAB Simulink model at different fixed and variable speed conditions. The sensitivity of the each proposed signal has been studied under different operating conditions. Measured and simulated results are presented, a comparison with the results from using stator current and total power has been addressed and the improvement in condition monitoring detection performance has been demonstrated in comparison with previous methods, looking at current, power and vibration analysis.

Item Type:Thesis (Doctoral)
Award:Doctor of Philosophy
Keywords:Wind Power, Condition Monitoring, Generator Fault detection, Generator Control.
Faculty and Department:Faculty of Science > Engineering and Computing Science, School of (2008-2017)
Thesis Date:2013
Copyright:Copyright of this thesis is held by the author
Deposited On:21 Nov 2013 11:18

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