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

Shoujun Yan, Lijie Zhou, Lifeng Song, Huiyu Guo, Junliang Wu, Run Luo () and Fuyu Zhao
Additional contact information
Shoujun Yan: China Institute of Nuclear Industry Strategy, Beijing 100048, China
Lijie Zhou: China Institute of Nuclear Industry Strategy, Beijing 100048, China
Lifeng Song: China Institute of Nuclear Industry Strategy, Beijing 100048, China
Huiyu Guo: School of Resource & Environment and Safety Engineering, University of South China, Hengyang 421001, China
Junliang Wu: School of Resource & Environment and Safety Engineering, University of South China, Hengyang 421001, China
Run Luo: School of Resource & Environment and Safety Engineering, University of South China, Hengyang 421001, China
Fuyu Zhao: School of Nuclear Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China

Energies, 2025, vol. 18, issue 3, 1-20

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 (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/3/567/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/3/567/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:3:p:567-:d:1576858

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().