Enhancing Frequency Regulation in Nuclear-Renewable Hybrid Energy Systems Through Optimally Configured FOPID Controllers and Adaptive Pelican Optimization Algorithm

This study has explored the application of Fractional Order Proportional-Integrator-Derivative (FOPID) controllers within Nuclear-Renewable Hybrid Energy Systems (N-RHES). N-R HES has played a pivotal role in the transition to decarbonized energy systems, holding substantial promise for establishing sustainable, carbon-free energy infrastructure in the near future. The investigation has focused on an N-R HES that incorporates diverse energy sources such as solar, wind, nuclear, fuel cell systems, Battery Energy Storage Systems (BESS), and Flywheel Energy Storage Systems (FESS). To achieve performance objectives, the study has employed various meta-heuristic algorithms, including the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Pelican Optimization Algorithm (POA), and Adaptive POA (APOA), to optimize the parameters of the FOPID controllers. Additionally, the research has introduced an enhanced version of the conventional POA, incorporating a velocity computation strategy to enhance the tuning capabilities of FOPID controllers. The results have indicated that optimally configured FOPID controllers effectively manage system frequency and ensure stability within the examined N-R HES. The incorporation of the velocity computation strategy in the POA has contributed to improved tuning performance for FOPID controllers. This study has highlighted the potential of advanced optimization techniques for achieving superior control strategies for N-R HES.