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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Shoujun Yan & Lijie Zhou & Lifeng Song & Huiyu Guo & Junliang Wu & Run Luo & Fuyu Zhao, 2025. "Collaborative Control and Intelligent Optimization of a Lead–Bismuth Cooled Reactor Based on a Modified PSO Method," Energies, MDPI, vol. 18(3), pages 1-20, January.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:3:p:567-:d:1576858
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    References listed on IDEAS

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    1. Mohamed Alwaeli & Viktoria Mannheim, 2022. "Investigation into the Current State of Nuclear Energy and Nuclear Waste Management—A State-of-the-Art Review," Energies, MDPI, vol. 15(12), pages 1-22, June.
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