NUCLEAR TECHNIQUES, Volume. 48, Issue 5, 050602(2025)
Setpoint decision of PWR control system based on particle swarm optimization algorithm
Analog-based instrumentation and control systems in nuclear power plants (NPP) are being progressively supplanted by comprehensive digital technologies, enabling the deployment of sophisticated and efficient advanced control methodologies. Although there are studies on improving the control performance of pressurized water reactor (PWR) NPP control systems by advanced control algorithms, most of them only focus on the control system itself without considering the interconnection and coupling among multiple control systems.
This study aims to propose a setpoint decision optimization system for coordinating multiple control systems from the top level to optimize the overall control performances and achieve better task execution results.
The intelligent decision system for PWR control system was optimized based on particle swarm optimization (PSO) method. Both the decision objective function and operation constraint conditions of the intelligent decision system were proposed. Considering the actual operation of PWR, the setpoint was optimized offline and the intelligent decision operation was performed online according to the operation condition to provide the directions and amplitudes of the control targets for the underlying control systems. Subsequently, the typical operation process of the PWR NPP was taken as an example to carry out the simulation of the designed PSO-based intelligent decision-making system, and the simulation results were compared with that of traditional setpoint decision method in term of Integral of Time multiplied by the Square Error (ITSE).
Compared with the control scheme using traditional setpoints, the ITSE values of average coolant temperature in primary loop, pressurizer fluid level, pressurizer pressure and steam generator fluid level obtained by optimized setpoint are decreased by 58.9%, 67.7%, 99.9% and 83.3%, respectively. The peak values are decreased by 62.4%, 3.0%, 100% and 66.3%, respectively.
The simulation results show that the system proposed in this study effectively reduce the ITSE and peak value of the system. The overall control performances and safety margin of the control systems of PWR NPP are improved.
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Qi ZHANG, Xianshan ZHANG, Peiwei SUN, Xinyu WEI. Setpoint decision of PWR control system based on particle swarm optimization algorithm[J]. NUCLEAR TECHNIQUES, 2025, 48(5): 050602
Category: NUCLEAR ENERGY SCIENCE AND ENGINEERING
Received: May. 23, 2024
Accepted: --
Published Online: Jun. 26, 2025
The Author Email: Peiwei SUN (孙培伟)