2026-10-10T16:14:19Z https://www.scidb.cn/oai

10.57760/sciencedb.hjs.00374 2025-04-01T13:55:01Z

2025-04-01 Optimization of power control parameters for molten salt reactor based on multi-objective particle swarm optimization algorithm doi:10.57760/sciencedb.hjs.00374 en Abstract [Background] Molten Salt Reactors (MSRs), distinguished by their inherent safety and flexible deployment, have a wide range of applications in various scenarios. Power control system (PCS) plays a critical role in ensuring the safe and stable operation of MSRs. [Purpose] This study aims to develop an advanced controller gains tuning method for PCS to simultaneously regulate reactor fuel temperature and achieve rapid load-following performance, addressing the demands of future composite energy systems. [Methods] The Proportional-Integral- Derivative (PID) controller, which is widely employed in reactor power control systems, is adopted to regulate the temperature and power of the Molten Salt Breeder Reactor (MSBR). A nonlinear model of the MSBR primary loop is developed using MATLAB/Simulink software. Based on the nonlinear model, Multi-Objective Particle Swarm Optimization (MOPSO) algorithm is adopted applied for tuning the controller gains. The sensitivity ratio deviation is introduced to automatically select Pareto-optimal solutions that balance competing control objectives. The tuned PID controllers are then evaluated under different working conditions. [Results] The results demonstrate that the tuned PID controllers with the MOPSO exhibit better load-following capability and achieve a balance between the power and temperature objectives. The system effectively suppresses overshoot to within 2% under step-change conditions, while maintaining rapid response speed and strong anti-interference ability [Conclusions] The proposed MOPSO-based tuning method has been proved to be a viable and efficient approach for optimizing PID controllers in MSR power control systems Molten salt reactor; Multiple objective particle swarm optimization; Power control; System simulation Qiu Zhiyi Wang Hexiang Li Minghai Zhu Guifeng Guo Jian Liu Yafen Yan Rui Zou Yang PUBLIC https://creativecommons.org/licenses/by-nc/4.0/ dataset Science Data Bank