Optimization of Nuclear Reactor Power with Control Rods Driven by Switched Reluctance Motor (SRM) With Differential Evolution and Firefly Algorithms

Over the previous few decades, bio-inspired (BI) organic process improvement techniques have experienced extraordinary popularity in the field of engineering. These techniques gift a troublesome competition to ancient numerical procedures that suffer from convexity and continuity assumptions and that usually use a gradient based mostly search that's sensitive to the initial resolution. Whereas initial BI techniques specially have been investigated by novel and improved variants. The population primarily based computing strategies are notably engaging for finding multi-objective (MO) problems due to their capability of producing an outsized variety of Pareto-optimal solutions in one run. In this paper, two algorithms of firefly and differential evolution concept is proposed as a performance metrics for switched reluctance motor (SRM) as control rod drive in small modular reactor. This work aims to prevail and amend the remarkable drawback of switched reluctance motor, which is torque ripple, by executed current control of the motor based on the PI controller in a closed-loop controller. Furthermore, the output power of the plant is optimized to trace the reference properly. The effectiveness and advantage of the system control scheme are presented in MATLAB software in real-time.