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Dynamic matrix control for thermal power of multi-modular high temperature gas-cooled reactor plants

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  • Jiang, Di
  • Dong, Zhe

Abstract

To suppress the fluctuation from both load side and intermittent renewable energy (IRE), nuclear power plants (NPPS) should be operated in load-following mode to improve economic competitiveness. The modular high temperature gas-cooled reactor (MHTGR) belongs to the category of small nuclear reactor (SMRs) and is suitable for load-following by the virtue of online refueling ability and inherent safety. To realize economies of scale for MHTGR, multi-modular scheme that multiple nuclear steam supply system (NSSS) modules are connected in parallel providing superheated steam for common turbine is recommended to achieve desired power ratings. However, because of the large heat capacity in the pebble-bed of MHTGR and thermal coupling of different NSSSs through common secondary loop fluid network, the current control strategy which suppresses the nuclear power, coolant temperatures measurement from their set-points without considering thermal dynamic of NSSS itself, may not favorable for heat transfer in the NSSS. To improve the load-following ability, a multivariable dynamic matrix control (DMC) is constituted to dynamic compensate the thermal energy variation of NSSS. The implementation of the DMC has a typical cascade structure, where DMC revises the set-points of NSSS module in outer loop and the existing PID control law is adopt for stabilization in inner loop. Numerical results show that this cascade DMC can improve the transient of thermal power under power maneuvering, and can also attenuate the nuclear power, helium flowrate set-points and feed-water temperature step disturbance.

Suggested Citation

  • Jiang, Di & Dong, Zhe, 2020. "Dynamic matrix control for thermal power of multi-modular high temperature gas-cooled reactor plants," Energy, Elsevier, vol. 198(C).
    • Handle: RePEc:eee:energy:v:198:y:2020:i:c:s036054422030493x
    DOI: 10.1016/j.energy.2020.117386
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    References listed on IDEAS

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    Cited by:

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    2. Zhe Dong & Zhonghua Cheng & Yunlong Zhu & Xiaojin Huang & Yujie Dong & Zuoyi Zhang, 2023. "Review on the Recent Progress in Nuclear Plant Dynamical Modeling and Control," Energies, MDPI, vol. 16(3), pages 1-19, February.
    3. Shi, Yao & Lin, Runze & Wu, Xialai & Zhang, Zhiming & Sun, Pei & Xie, Lei & Su, Hongye, 2022. "Dual-mode fast DMC algorithm for the control of ORC based waste heat recovery system," Energy, Elsevier, vol. 244(PA).
    4. Cui, Chengcheng & Zhang, Junli & Shen, Jiong, 2023. "System-level modeling, analysis and coordinated control design for the pressurized water reactor nuclear power system," Energy, Elsevier, vol. 283(C).
    5. Hui, Jiuwu & Lee, Yi-Kuen & Yuan, Jingqi, 2023. "ESO-based adaptive event-triggered load following control design for a pressurized water reactor with samarium–promethium dynamics," Energy, Elsevier, vol. 271(C).
    6. Dong, Zhe & Li, Bowen & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2022. "Power-pressure coordinated control of modular high temperature gas-cooled reactors," Energy, Elsevier, vol. 252(C).
    7. Hui, Jiuwu, 2024. "Discrete-time integral terminal sliding mode load following controller coupled with disturbance observer for a modular high-temperature gas-cooled reactor," Energy, Elsevier, vol. 292(C).
    8. Hui, Jiuwu & Yuan, Jingqi, 2022. "Neural network-based adaptive fault-tolerant control for load following of a MHTGR with prescribed performance and CRDM faults," Energy, Elsevier, vol. 257(C).
    9. Hui, Jiuwu & Yuan, Jingqi, 2022. "Load following control of a pressurized water reactor via finite-time super-twisting sliding mode and extended state observer techniques," Energy, Elsevier, vol. 241(C).
    10. Wu, Shifa & Ma, Xiaolong & Liu, Junfeng & Wan, Jiashuang & Wang, Pengfei & Su, G.H., 2023. "A load following control strategy for Chinese Modular High-Temperature Gas-Cooled Reactor HTR-PM," Energy, Elsevier, vol. 263(PA).
    11. Zhang, Tianhao & Dong, Zhe & Huang, Xiaojin, 2024. "Multi-objective optimization of thermal power and outlet steam temperature for a nuclear steam supply system with deep reinforcement learning," Energy, Elsevier, vol. 286(C).
    12. Hui, Jiuwu & Yuan, Jingqi, 2021. "Chattering-free higher order sliding mode controller with a high-gain observer for the load following of a pressurized water reactor," Energy, Elsevier, vol. 223(C).

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