Abstract
The growing integration of renewable energy sources in hybrid microgrid systems necessitates effective frequency stability controllers. This paper presents a thorough comparison of Cuckoo Search Optimization (CSO), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Proportional-Integral-Derivative (PID) controllers in a realistic 20 kW hybrid microgrid environment. Through meticulous simulations, tuning parameters for each method are fine-tuned for optimal performance. The study quantitatively evaluates critical metrics, including lagging time, overshoot, settling time, and steady-state error, providing insights into the strengths and weaknesses of each approach. The paper introduces a percentage improvement analysis, showcasing advancements made by each method. The outcomes serve as a benchmark for practical implementation, aiding in the selection of the most suitable controller tuning method for achieving enhanced frequency stability in hybrid microgrid systems.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
