Research on Optimization Control of Nuclear Power Plant Coordination System Based on ESO-MPC

Guo Yongfei; Zhang Rongbin; Yao Zhiyuan; Lang Yukai; Zhao Jiayu

doi:10.13832/j.jnpe.2024.06.0178

Volume 45 Issue 6

Dec. 2024

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Article Navigation > Nuclear Power Engineering > 2024 > 45(6): 178-184

Guo Yongfei, Zhang Rongbin, Yao Zhiyuan, Lang Yukai, Zhao Jiayu. Research on Optimization Control of Nuclear Power Plant Coordination System Based on ESO-MPC[J]. Nuclear Power Engineering, 2024, 45(6): 178-184. doi: 10.13832/j.jnpe.2024.06.0178

Citation:

Guo Yongfei, Zhang Rongbin, Yao Zhiyuan, Lang Yukai, Zhao Jiayu. Research on Optimization Control of Nuclear Power Plant Coordination System Based on ESO-MPC[J]. Nuclear Power Engineering, 2024, 45(6): 178-184. doi: 10.13832/j.jnpe.2024.06.0178

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Research on Optimization Control of Nuclear Power Plant Coordination System Based on ESO-MPC

doi: 10.13832/j.jnpe.2024.06.0178

1.
China Nuclear Power Technology Research Institute Co., Ltd., Shenzhen, Guangdong, 518000, China
2.
School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China

Received Date: 2024-02-21
Rev Recd Date: 2024-04-12
Publish Date: 2024-12-17

Abstract

Abstract

The regulation characteristics of nuclear island and conventional island are quite different, so it is necessary to coordinate the synchronous control of nuclear island and conventional island to achieve better control effect. It is of great significance to study the optimal control strategy of coordinated control system. In this paper, a model predictive control (MPC) algorithm based on extended state observer (ESO) is proposed to solve the problem that the coordinated control system of nuclear power plant is prone to disturbance. The proposed method accurately estimates the external disturbance by using ESO, and then integrates the disturbance estimation value into the rolling optimization process of MPC to realize the adaptive correction of the prediction model, thereby obtaining the required optimization control rate. In the simulation experiment, the algorithm proposed in this paper was compared with the performance of proportional integral differential control and multivariable model predictive controller, and the results showed that the algorithm proposed in this paper had good performance. In the scenario of unit load setting disturbance, the mean square error of main steam pressure and unit load by the proposed algorithm is 0.06 and 0.02 respectively, which is significantly better than the other two algorithms. The algorithm proposed in this paper can enable the coordinated control system of nuclear power units to achieve precise control performance in the presence of external disturbances.
- Nuclear power unit,
- Coordinated control,
- Model predictive control (MPC),
- Extended state observer (ESO),
- Perturbation error

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References(23)

References

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