In this study, the parameters of commonly used Proportional–Integral (PI) and Proportional–Integral–Derivative (PID) controllers were optimized using the Chaos‑Embedded Adaptive Particle Swarm Optimization (CEAPSO) algorithm. The controllers’ performances were compared under variable and uncertain wind conditions; the PID controller was found to achieve approximately 77% lower control error and 52.9% faster system stabilization than the PI controller. Furthermore, the PID‑based controller more effectively reduced power output fluctuations, achieved faster transient stabilization, and minimized dynamic loads, thereby significantly lowering maintenance costs and the risk of mechanical wear. The high tuning accuracy of CEAPSO not only improved control performance but also substantially enhanced turbine power quality and operational reliability. These results demonstrate that optimization‑based parameter tuning provides meaningful technical and economic benefits, making the study a valuable reference for developing control strategies and improving energy efficiency in renewable energy systems.
Soner Çelikdemir (Wed,) studied this question.