Impact of Load Variations on the Stability of GA -Optimized PID Controllers in Isolated Power Systems

Sustaining stable and optimum power system performance is crucial for dependable energy grid operation. This study investigates the performance of a Genetic Algorithm (GA)-optimized Proportional-Integral-Derivative (PID) controller under varying load conditions in power systems. The controller was specifically tuned and optimized for a 0.2 per unit (pu) load increment, equivalent to 50 MW, using GA parameters tailored for optimal performance. We analyze performance metrics such as rise time, settling time, overshoot, undershoot, peak response, and stability for load increments (25 MW to 55 MW) and decrements (−25 MW to −50 MW). Results demonstrate that the G A -optimized PID controller achieves fast response times and minimal overshoot for smaller load variations (25 MW, 30 MW), maintaining stability. However, for larger load changes (35 MW to 55 MW), the controller exhibits increased settling times, higher oscillations, and reduced stability, reflected in overshoot and undershoot metrics. These findings highlight the controller's sensitivity to load dynamics and underscore the need for adaptive control strategies in mitigating performance degradation under varying load conditions. Future research could explore advanced PID tuning methods or adaptive control algorithms to enhance the controller's robustness across a wider range of load fluctuations in power systems.