Power System Stabilizer Implementation Using Fuzzy Logic Controller

The Power System Stabilizer (PSS) is a critical control device designed to enhance power system stability by damping low-frequency oscillations. As an integral component of the Automatic Voltage Regulator (AVR) system, the PSS maintains grid voltage within specified operational limits. Recent advancements have demonstrated the effectiveness of Fuzzy Logic Controllers (FLCs) in PSS applications, particularly due to their robustness in handling system nonlinearities and operational uncertainties. In implementation, the FLC-based PSS typically processes multiple sensor inputs (such as rotor speed deviations and power angle variations) through a structured fuzzy inference system. The core algorithm involves three key stages: fuzzification of input signals using membership functions, rule evaluation through a predefined knowledge base, and defuzzification to generate precise control signals. A typical code implementation would utilize triangular or Gaussian membership functions for input variables, with rule bases containing 20-50 IF-THEN statements defining control strategies. The control output from the FLC is then fed to the AVR system, where it modulates excitation signals to dampen oscillations. This approach has proven superior to conventional PID-based stabilizers, especially during system disturbances, with simulation results showing improved transient stability and reduced settling times. MATLAB/Simulink implementations commonly use the Fuzzy Logic Toolbox for system modeling, with real-world deployments often involving DSP or FPGA platforms for high-speed processing.