Experimental Validation of an Optimized Microcontroller-Based Power System Stabilizer for Small-Signal Stability Enhancement with Unknown Generator Parameter Estimation

The small-signal stability of modern power systems presents a significant challenge, particularly due to the uncertainties associated with machine parameters, which further highlights the importance of addressing this issue. Additionally, the traditional power system stabilizer (PSS) design relies heavily on machine parameters, which emphasizes the importance of accurate parameter estimation of synchronous machines (SM). On the other hand, real-time digital simulators (RTDS) offer great potential for rapid prototyping, testing, and validation; they often ignore critical aspects such as delays associated with physical channels, non-ideal components, and environmental effects. These issues make RTDS a powerful tool for concept validation, and the actual performance requires in-field testing where machine parameters play a vital role in determining the controller's behavior. Therefore, this paper addresses the suppression of small-signal oscillations under unknown parameters of SM. A microprocessor-based proportional integral derivative (PID)-PSS prototype is introduced. The Moth Flame Optimization (MFO) algorithm is adopted in this study to optimize the controller’s gains. The objective function is based on the Integral Time Absolute Error (ITAE). In addition, to ensure this work's replicability and real-world applicability, the necessary tests for determining machine parameters, based on IEC standards, are summarized. The experimental investigation of the proposed Power System Stabilizer (PSS) demonstrates its effectiveness in damping system oscillations, achieving a settling time of 6.5 seconds with a 0.1 per-unit (p.u.) overshoot under a 15% step change in load, and a settling time of 12 seconds with a 0.16 (p.u.) overshoot under a 30% load variation.