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NSGA-II algorithm based control parameters optimization strategy for megawatt novel nuclear power systems

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  • Jiang, Qingfeng
  • Wang, Pengfei

Abstract

The megawatt novel nuclear power system (MNNPS) of heat-pipe reactor coupled with supercritical carbon dioxide (sCO2) Brayton cycle is the critical research topic, and its control system plays an important role for its safety. However, there are very few studies on the optimization of MNNPS control parameters. Obtaining the best control parameters under specified control system structures is an important way to improve the safety of MNNPS. In this paper, a NSGA-II algorithm based control parameters optimization strategy for MNNPS is proposed. Firstly, the sensitivity analysis of control parameters was carried out to analyze the coupling effect between the system-controlled parameters. Subsequently, bi-objective and tri-objective control parameter optimization strategies were proposed for MNNPS, under which NSGA-II algorithm was used to optimize the control system parameters of MNNPS sequentially. Finally, to verify the effectiveness of the proposed optimization strategies, dynamic simulations of the MNNPS under typical transient conditions such as step and ramp load change transients were simulated. The simulation results demonstrate the effectiveness of the two optimization strategies, and the superiority of the tri-objective optimization strategy over the bi-objective optimization strategy. This paper can provide theoretical support for the optimization of MNNPS control system parameters.

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  • Jiang, Qingfeng & Wang, Pengfei, 2025. "NSGA-II algorithm based control parameters optimization strategy for megawatt novel nuclear power systems," Energy, Elsevier, vol. 316(C).
    • Handle: RePEc:eee:energy:v:316:y:2025:i:c:s0360544225000866
    DOI: 10.1016/j.energy.2025.134444
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    References listed on IDEAS

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    1. Wang, Haotong & Shi, Jianxin & Lin, Chaojing & Liu, Xinmeng & Li, Guolong & Sun, Shengdi & Zhou, Xin & Li, Yanjun, 2025. "Nuclear power systems unsupervised anomaly localization considering spatiotemporal information and influence mechanism between devices," Energy, Elsevier, vol. 325(C).

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