Reactive Power-Based Adaptive Fuzzy Stabilizer for DFIG Wind Farms in High-Renewable Power Systems

The increasing integration of renewable energy sources into modern power systems has intensified transient stability challenges, particularly under severe fault conditions. This paper proposes an intelligent data-driven fuzzy power system stabilizer (FPSS) for doubly-fed induction generator (DFIG)–based wind farms to enhance rotor angle stability in power grids with high renewable penetration. The proposed controller incorporates an adaptive fuzzy inference system with online parameter tuning based on real-time grid measurements, enabling continuous adjustment to changing operating conditions. The FPSS is embedded within the reactive power control loop of the DFIG and utilizes frequency deviation and its rate of change at the point of common coupling as input signals. Simulation studies conducted on a modified IEEE 9-bus system with about 30% wind penetration, considering multiple fault scenarios, demonstrate that the proposed FPSS significantly improves oscillation damping performance, reduces rotor angle settling time by up to 50% and increases the critical clearing time (CCT) by more than 20% compared to conventional power system stabilizer (CPSS). Thus, the results confirm the effectiveness and adaptability of the proposed approach for enhancing transient stability under realistic, time-varying operating conditions in renewable-rich power systems.