A multi-objective co-optimization method of controller parameters for the overall system of small pressurized water reactor

Small pressurized water reactors (SPWRs) normally have complicated and varying working conditions, and become an important direction for nuclear energy development. The overall system of SPWR, including the reactor coolant average temperature control system, the feedwater control system of the once-through steam generator (OTSG), the steam turbine speed control system and the steam dump control system, is used to guarantee the safe and stable operation. The overall system of SPWR is designed with multiple PI controllers. To accomplish intelligent self-tuning of PI controller parameters, reduce the dependence on human engineering experience, and improve the control performance of the overall system, a multi-objective co-optimization method(MMOCO) with PI controller parameters for overall system of SPWR is proposed. Firstly, based on the coordinated control theory and PI control algorithm, the overall system of SPWR is established. Then, a MMOCO for the overall system of SPWR is designed with the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II). Finally, to compare the performance of the controller parameters derived from the MMOCO and the controller parameters obtained via the engineering tuning method, step load decrease transients are selected. The results show that the ability to control the overall system of SPWR is effectively improved after applying the MMOCO.