Multi-objective optimization of control parameters for a pressurized water reactor pressurizer using a genetic algorithm

Abstract This paper presents the multi-objective optimization of control parameters for a pressurized water reactor (PWR) pressurizer using a genetic algorithm. Firstly, a widely-used nonequilibrium three-region pressurizer model is adopted to describe dynamic behavior of the pressurizer during transient operations. Then, a pressure and water level control strategy of the pressurizer employing proportional-integral-derivative (PID) controllers is introduced and analyzed, which uses a spray valve and two electric heaters for pressure control and regulates charging flowrate with letdown flowrate keeping constant for water level control. With implementation of the pressurizer model and control strategy, a control simulation platform of the pressurizer is developed in MATLAB/Simulink environment. Based on the simulation platform, the non-dominated sorting genetic algorithm II (NSGA-II) is applied for the multi-objective optimization of the PID controllers’ parameters in the pressure and water level control systems of the pressurizer, respectively, with multi-objective functions defined as the control performance obtained and the control cost required. Fitness values of the multi-objective functions are generated based on simulation results of the pressurizer during a 100% of full power (FP) to 25% FP load rejection transient in each iteration step of the optimization. Two Pareto fronts consisting of non-dominated optimal solutions are obtained for two multi-objective optimization problems for the pressure and water level control systems. Five typical points on each Pareto front are chosen for the corresponding multi-objective optimization problem. Dynamic responses of the pressurizer employing the optimal control parameters at these points are compared with those using original design control parameters, under a 100% FP to 90% FP step load decrease transient, a 90% FP to 100% FP step load increase transient and the above load rejection transient. Based on the comparison results, optimum parameters are chosen for the pressure and water level control systems. It has been demonstrated that the control systems with these optimum parameters can keep good balance between maximizing control performance and minimizing control cost of the pressurizer, which contributes to the improvement of system responses with reduced mechanical wear and fatigue risk of corresponding actuators.