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Energies
Volume 18
Issue 3
10.3390/en18030567
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Collaborative Control and Intelligent Optimization of a Lead–Bismuth Cooled Reactor Based on a Modified PSO Method

by
Shoujun Yan
1,
Lijie Zhou
1,
Lifeng Song
1,
Huiyu Guo
2,
Junliang Wu
2,
Run Luo
2,* and
Fuyu Zhao
3
1
China Institute of Nuclear Industry Strategy, Beijing 100048, China
2
School of Resource & Environment and Safety Engineering, University of South China, Hengyang 421001, China
3
School of Nuclear Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China
*
Author to whom correspondence should be addressed.
Energies 2025, 18(3), 567; https://doi.org/10.3390/en18030567
Submission received: 13 December 2024 / Revised: 18 January 2025 / Accepted: 19 January 2025 / Published: 25 January 2025
(This article belongs to the Special Issue Advanced Technologies in Nuclear Engineering)
Versions Notes

Abstract

Accelerator-driven subcritical (ADS) reactors with lead–bismuth eutectic (LBE) coolants are some of the Gen-IV nuclear energy systems that can generate clean electricity and potentially transmute spent fuel. The dynamic characteristics and control strategy of an ADS reactor are substantially different from those of traditional nuclear reactors. In this paper, a new collaborative control strategy is proposed using an accelerator beam and a control rod, and the control system’s parameters are optimized using a modified particle swarm optimization (PSO) method. To test the control performance, a simulation platform is developed with a nonlinear reactor dynamic model, a power compensation control system and a coolant temperature control system. Four typical control transients are used, including a ±10% full-power (FP) step change load and a ±5% FP/min linear variable load. The simulation results show that the collaborative control strategy has a better load tracking capability and a higher power control accuracy than the beam single-control strategy and the rod single-control strategy. The results also show that the performance of the collaborative control system in terms of the reactor’s power and coolant temperature is significantly improved based on the modified PSO parameter optimization.
Keywords: LBE-cooled reactor; nonlinear reactor dynamic model; collaborative control; particle swarm optimization LBE-cooled reactor; nonlinear reactor dynamic model; collaborative control; particle swarm optimization

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MDPI and ACS Style

Yan, S.; Zhou, L.; Song, L.; Guo, H.; Wu, J.; Luo, R.; Zhao, F. Collaborative Control and Intelligent Optimization of a Lead–Bismuth Cooled Reactor Based on a Modified PSO Method. Energies 2025, 18, 567. https://doi.org/10.3390/en18030567

AMA Style

Yan S, Zhou L, Song L, Guo H, Wu J, Luo R, Zhao F. Collaborative Control and Intelligent Optimization of a Lead–Bismuth Cooled Reactor Based on a Modified PSO Method. Energies. 2025; 18(3):567. https://doi.org/10.3390/en18030567

Chicago/Turabian Style

Yan, Shoujun, Lijie Zhou, Lifeng Song, Huiyu Guo, Junliang Wu, Run Luo, and Fuyu Zhao. 2025. "Collaborative Control and Intelligent Optimization of a Lead–Bismuth Cooled Reactor Based on a Modified PSO Method" Energies 18, no. 3: 567. https://doi.org/10.3390/en18030567

APA Style

Yan, S., Zhou, L., Song, L., Guo, H., Wu, J., Luo, R., & Zhao, F. (2025). Collaborative Control and Intelligent Optimization of a Lead–Bismuth Cooled Reactor Based on a Modified PSO Method. Energies, 18(3), 567. https://doi.org/10.3390/en18030567

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