Online PID Parameter Optimization Using Genetic Algorithm for a Wind Power Generation System
DOI:
https://doi.org/10.4108/eetsmre.11140Keywords:
Genetic Algorithm, PID controller, online optimization, wind power generation, anti-windup controlAbstract
INTRODUCTION: In wind power generation systems, the unstable variability of wind energy significantly affects control quality and power stability. Conventional PID controllers often show limitations in nonlinear systems or systems with time-varying parameters, especially when integral windup and degraded transient performance occur.
OBJECTIVES: This paper proposes an online optimization method for PID parameters based on a Genetic Algorithm (GA), applied to a simplified dynamic model of a wind power generation system, in order to improve the system response quality.
METHODS: The studied system is modeled by a second-order transfer function representing the system’s inertia and friction characteristics. The GA is implemented in a real-time optimization manner, using an objective function based on the ITAE criterion to evaluate and select the optimal PID parameter set.
RESULTS: Simulation results show that the proposed online GA–PID approach improves settling time, reduces overshoot, and eliminates steady-state error more effectively than fixed PID and conventional anti-windup PID controllers.
CONCLUSION: The proposed online GA–PID method is suitable for energy systems with high variability and adaptive control requirements, especially in wind power generation applications.
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