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Practical dynamic matrix control of MHTGR-based nuclear steam supply systems

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  • Jiang, Di
  • Dong, Zhe

Abstract

To balance the intermittent renewable energy and cope with the increasing nuclear power installed capacity in China, it is necessary for nuclear power plants (NPPs) to operate with load-following mode for enhancing economic competitiveness. The modular high temperature gas-cooled reactor (MHTGR) is an appropriate candidate for load-following operation due to the advanced features such as robust fuel elements, online fueling and full-power-range temperature negative feedback. The MHTGR-based nuclear steam supply systems (NSSS) which produces superheated steam flow for electricity, is the core for any NPPs. The proper control of NSSS is the prerequisite for the safe, stable and efficient load-following operation. However, in current engineering practice, the set-point trajectories of neutron flux, primary coolant temperature, primary and secondary flowrates are just the curves by linking the referenced steady values from the thermal hydraulic design, which are further determined by the thermal power requirement. Thus, it is meaningful to investigate an optimization-oriented control method to improve the operation efficiency. Motivated by this, two dynamic matrix control (DMC) with cascade structure are presented to improve both thermal power and steam temperature of the MHTGR-based NSSS. The thermal power is optimized by the first DMC through adjusting the set-point of nuclear flux. The second DMC is then designed based on the integration of the NSSS, the proportional-integral-derivative (PID) and the first DMC to improve the steam temperature response by adjusting the feed-water flowrate. The control performance during wide range operation is shown and discussed with the simulation results of a large-scale MHTGR plant model.

Suggested Citation

  • Jiang, Di & Dong, Zhe, 2019. "Practical dynamic matrix control of MHTGR-based nuclear steam supply systems," Energy, Elsevier, vol. 185(C), pages 695-707.
    • Handle: RePEc:eee:energy:v:185:y:2019:i:c:p:695-707
    DOI: 10.1016/j.energy.2019.07.088
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Dong, Zhe & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2020. "Multilayer perception based reinforcement learning supervisory control of energy systems with application to a nuclear steam supply system," Applied Energy, Elsevier, vol. 259(C).
    3. Dong, Zhe & Cheng, Zhonghua & Zhu, Yunlong & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2023. "Coordinated control of mHTGR-based nuclear steam supply systems considering cold helium temperature," Energy, Elsevier, vol. 284(C).
    4. 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).
    5. 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).
    6. 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).
    7. 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).
    8. 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).
    9. 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).
    10. 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).
    11. 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).

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