Abstract
This paper deals with the current sensor fault diagnosis and isolation (FDI) problem for a permanent magnet synchronous generator (PMSG) based wind system. An observer based scheme is presented to detect and isolate both additive and multiplicative faults in current sensors, under varying torque and speed. This scheme includes a robust residual generator and a fault estimation based isolator. First, the PMSG system model is reformulated as a linear parameter varying (LPV) model by incorporating the electromechanical dynamics into the current dynamics. Then, polytopic decomposition is introduced for H ∞ design of an LPV residual generator and fault estimator in the form of linear matrix inequalities (LMIs). The proposed gain-scheduled FDI is capable of online monitoring three-phase currents and isolating multiple sensor faults by comparing the diagnosis variables with the predefined thresholds. Finally, a MATLAB/SIMULINK model of wind conversion system is established to illustrate FDI performance of the proposed method. The results show that multiple sensor faults are isolated simultaneously with varying input torque and mechanical power.
Highlights
Due to the high power density and efficiency, permanent magnet synchronous generator based wind turbines are promising in wind conversion systems (WECSs) with variable speed operation and full-scale power delivery [1,2]
To illustrate the proposed model based fault diagnosis for current sensor in machine side converter, a MATLAB/SIMULINK (Version R2018a, MathWorks Inc., Natick, MA, USA) model is developed referring to the real laboratory prototype
Both the wind conversion system and fault diagnosis algorithm are implemented in the SIMULINK environment
Summary
Due to the high power density and efficiency, permanent magnet synchronous generator based wind turbines are promising in wind conversion systems (WECSs) with variable speed operation and full-scale power delivery [1,2]. A sensor FDI in [7] that a bank of observers are designed to generate residuals sensitive to sensor fault for DFIG based WECSs requires open-loop operation until the fault is isolated. In [9], the nonlinear model of DFIG is transformed into a Takagi–Sugeno (T-S) fuzzy model and a bank of observers based on the model are presented to generate residuals for sensor fault detection and isolation To deal with both additive and multiplicative sensor faults, a generalized observer scheme is presented in [10] by combining H_/H∞ filter with Kalman-like observer for DFIG systems. An observer based scheme is presented to detect and isolate both additive and multiplicative faults in current sensors under varying torque and speed.
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