Optimized PID Controller Model based on Genetic Algorithm for Pressurized Water Reactor (PWR)

In the commercial power generation race among several nuclear reactors, the most widely used reactor model globally is the Pressurized Water Reactor (PWR). The Genetic Algorithm (GA)-based model of an improved Proportional-Integral-Derivative (PID) controller for PWR is studied here. PWRs are the best type of nuclear energy source to produce commercial electrical energy all over the planet. The reactor core reactivity can be controlled by several safety components of which the reactor control rod is dominant and reliable. The control rod is one of the most important components for managing reactor power levels. The basic point-kinetics equations are utilized to develop the reactor model, which combines reactivity feedback and thermal-hydraulic factors. At different levels of reactor power, the reactor model is linearized. Controls for power levels should be exceedingly precise and quick. Therefore, controller tuning is crucial for achieving the best performance. The linear model parameters vary significantly, and an enhanced PID controller system takes these differences into account at various power levels. A Fixed PID (FPID) controller and the suggested controller's effectiveness are compared. The outcomes show that the suggested control strategy outperforms traditional FPID.