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Modeling and control of nuclear reactor cores for electricity generation: A review of advanced technologies

Author

Listed:
  • Li, Gang
  • Wang, Xueqian
  • Liang, Bin
  • Li, Xiu
  • Zhang, Bo
  • Zou, Yu

Abstract

This investigation is to review advanced technologies for modeling and control of reactor cores in nuclear power plants for electricity generation. A reactor core in a nuclear power plant is the key part as the hot source with radioactivity nuclear fuel, which possesses security risks and economic potential. Incapacity of a nuclear power plant to carry out desired control of its core can result in either higher operating costs or a reduction in system security and reliability, and the implementation of desirable control for the core can improve security and effectiveness of the nuclear power plant. Generally speaking, the reactor core control contains the power (or coolant temperature) control and axial power difference (namely power distribution) control of the core. The core power control is to regulate the core power, and the core load following control is to regulate the core power and axial power difference simultaneously. Modeling reactor cores is the inevitable preliminary work for research of reactor core control. Over the decades, continuous work has been devoted to the research of including modeling, power and load following control for reactor cores. In this paper, the review on advanced technologies for modeling, power and load following control of reactor cores is presented. Modeling approaches for reactor cores are reviewed such as the point reactor core modeling. Power control methods for reactor cores are reviewed such as the feedback control with a state observer. Load following control techniques for reactor cores are reviewed such as Mode A, Mode G, Mode T, Mechanical Shim and advanced control methods of containing multivariable frequency control, etc. The review in this paper can contribute to comprehend the past work with respective advantages, and then exploit novel research directions for development of nuclear power plants.

Suggested Citation

  • Li, Gang & Wang, Xueqian & Liang, Bin & Li, Xiu & Zhang, Bo & Zou, Yu, 2016. "Modeling and control of nuclear reactor cores for electricity generation: A review of advanced technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 116-128.
  • Handle: RePEc:eee:rensus:v:60:y:2016:i:c:p:116-128
    DOI: 10.1016/j.rser.2016.01.116
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    References listed on IDEAS

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    1. Rowinski, Marcin Karol & White, Timothy John & Zhao, Jiyun, 2015. "Small and Medium sized Reactors (SMR): A review of technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 643-656.
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    Cited by:

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    2. Zhe Dong & Miao Liu & Di Jiang & Xiaojin Huang & Yajun Zhang & Zuoyi Zhang, 2018. "Automatic Generation Control of Nuclear Heating Reactor Power Plants," Energies, MDPI, vol. 11(10), pages 1-18, October.
    3. Dong, Zhe & Li, Bowen & Li, Junyi & Guo, Zhiwu & Huang, Xiaojin & Zhang, Yajun & Zhang, Zuoyi, 2021. "Flexible control of nuclear cogeneration plants for balancing intermittent renewables," Energy, Elsevier, vol. 221(C).
    4. 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).
    5. Hui, Jiuwu & Lee, Yi-Kuen & Yuan, Jingqi, 2023. "Load following control of a PWR with load-dependent parameters and perturbations via fixed-time fractional-order sliding mode and disturbance observer techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(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. Dong, Zhe & Liu, Miao & Zhang, Zuoyi & Dong, Yujie & Huang, Xiaojin, 2019. "Automatic generation control for the flexible operation of multimodular high temperature gas-cooled reactor plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 11-31.
    8. Michaelson, D. & Jiang, J., 2021. "Review of integration of small modular reactors in renewable energy microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    9. 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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