SPSA-based Performance Optimization Method for Steam Generator MPC System

Geng Pengcheng; Shi Changqing; Kong Xiangsong; Liu Hang; Liu Jiabin; Jiang Shaobo

doi:10.13832/j.jnpe.2022.05.0168

Volume 43 Issue 5

Oct. 2022

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Geng Pengcheng, Shi Changqing, Kong Xiangsong, Liu Hang, Liu Jiabin, Jiang Shaobo. SPSA-based Performance Optimization Method for Steam Generator MPC System[J]. Nuclear Power Engineering, 2022, 43(5): 168-175. doi: 10.13832/j.jnpe.2022.05.0168

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Geng Pengcheng, Shi Changqing, Kong Xiangsong, Liu Hang, Liu Jiabin, Jiang Shaobo. SPSA-based Performance Optimization Method for Steam Generator MPC System[J]. Nuclear Power Engineering, 2022, 43(5): 168-175. doi: 10.13832/j.jnpe.2022.05.0168

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SPSA-based Performance Optimization Method for Steam Generator MPC System

doi: 10.13832/j.jnpe.2022.05.0168

1.
State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment, China Nuclear Power Engineering Co., Ltd., Shenzhen, Guangdong, 518172, China
2.
Xiamen University of Technology, Xiamen, Fujian, 361021, China

Received Date: 2021-09-26
Rev Recd Date: 2021-11-16
Publish Date: 2022-10-12

Abstract

Abstract

The level change process of steam generator (SG) in nuclear power plant has strong nonlinearity and the phenomenon of "false water level" exists. Traditional SG level control systems mostly use fixed-parameter proportional-integral-derivative (PID) controllers, but traditional PID control methods do not have the capabilities of self-optimization, self-adaptation, and self-learning, making it difficult to achieve and maintain optimal control system performance. In order to improve the transient response ability of the unit and the stability, safety and economy of the nuclear power plant, a model predictive control (MPC) strategy based on simultaneous perturbation stochastic approximation (SPSA) algorithm is proposed. In this method, MPC system is used to replace the traditional PID control system, and SPSA is used to optimize and set the parameters of the level control system, so as to optimize the performance of the SG level control system. The simulation results show that this method can effectively improve the setting efficiency of SG level control parameters and the stability of the control system.

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References(23)

References

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