Active Fault-Tolerant Control for DFIG-Based Wind Energy Conversion Systems Using a Sensor FDI and a Novel Reconfiguration Framework

Doubly Fed Induction Generator (DFIG)-based Wind Energy Conversion Systems (WECSs) rely on accurate sensor measurements to ensure stable operation and effective power conversion. However, sensor faults can compromise control performance and system reliability and lead to unscheduled shutdowns if they are not promptly detected and accommodated. This paper presents an Active Fault-Tolerant Control (AFTC) framework for a grid-connected DFIG-based WECS, integrating an existing sensor Fault Detection and Isolation (FDI) methodology with a novel control reconfiguration framework. The inherited FDI module detects and isolates sensor faults, while the proposed reconfiguration framework automatically selects an appropriate compensation strategy according to the number of simultaneously faulty sensors. Pure Measurement Compensation (PMC), Hybrid Measurement-Estimation Compensation (HMEC), and Pure Estimation Compensation (PEC) are employed for single-, double-, and triple-sensor fault scenarios, respectively. These strategies replace or reconstruct faulty sensor measurements within the affected control loops using available healthy or estimated signals. The proposed framework is implemented in MATLAB/Simulink and evaluated under additive and multiplicative sensor fault scenarios. The decision function reaches the detection threshold approximately 0.4 ms after fault injection, while the effective fault identification and isolation signal is activated within approximately 2.4 ms, followed by the activation of the corresponding compensation strategy. The simulation results demonstrate that the proposed reconfiguration strategies for the AFTC framework maintain continuous converter operation and satisfactory dynamic performance following fault diagnosis. The proposed framework provides a structured approach to active control reconfiguration for improved reliability and resilience to faults in DFIG-based WECSs.