Abstract
This paper investigates the applications of Proportional-Integrator-Derivative (PID) and Fractional Order PID (FOPID) controllers in Nuclear-Renewable Hybrid Energy Systems (N-R HESs). The N-R HES is a recent technology in the area of decarbonized energy systems. N-R HESs are expected to contribute immensely to providing carbon-free and sustainable energy infrastructure in the upcoming days. It is also anticipated that system resiliency will be the primary concern when nuclear reactors are incorporated with intermittent renewable energy resources. Therefore, in this research, the authors intend to evaluate the compatibility of two classical controllers, PID and FOPID, to ensure the stability of N-R HESs. The N-R HES of this paper consists of different energy sources, such as solar, wind, nuclear, fuel cell systems, Battery Energy Storage Systems (BESS), and Flywheel Energy Storage Systems (FESS). To encounter system performance requirements, the PID and FOPID controller parameters are adjusted using a metaheuristic algorithm, namely Artificial-Bee-Colony (ABC) optimization algorithm. Metaheuristic optimization algorithms always do not guarantee global maxima/minima. Hence, another metaheuristic optimization algorithm, Teaching-Learning-based Optimization (TLBO), is used to validate the results. The results clearly show that the optimal PID and FOPID controllers can handle the system frequency and maintain the stability of the studied N-R HES.