Parameter evaluation of pressurized water reactor nuclear power unit’s dynamic model

LIU Dichen; WANG Li; ZHAO Jie; ZHANG Shengfeng; WU Guoyang; WANG Jun; SHAO Youguo

doi:10.16081/j.issn.1006-6047.2018.10.007

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Parameter evaluation of pressurized water reactor nuclear power unit’s dynamic model

更新时间：2025-04-25

- Parameter evaluation of pressurized water reactor nuclear power unit’s dynamic model
- Vol. 38, Issue 10, Pages: 39-45(2018)
- 作者机构：
  
  1. 武汉大学电气工程学院
  2. 长沙理工大学电气与信息工程学院
  3. 中国电力科学研究院
- 作者简介：
- 基金信息：
- DOI：10.16081/j.issn.1006-6047.2018.10.007
  CLC： TM623.91
- Published：2018
- 稿件说明：
移动端阅览
[1]刘涤尘,王力,赵洁,张胜峰,吴国旸,王骏,邵尤国.压水堆核电机组动态模型参数评价[J].电力自动化设备,2018,38(10):39-45.

LIU Dichen, WANG Li, ZHAO Jie, et al. Parameter evaluation of pressurized water reactor nuclear power unit’s dynamic model[J]. 2018, 38(10): 39-45.
[1]刘涤尘,王力,赵洁,张胜峰,吴国旸,王骏,邵尤国.压水堆核电机组动态模型参数评价[J].电力自动化设备,2018,38(10):39-45. DOI： 10.16081/j.issn.1006-6047.2018.10.007.

LIU Dichen, WANG Li, ZHAO Jie, et al. Parameter evaluation of pressurized water reactor nuclear power unit’s dynamic model[J]. 2018, 38(10): 39-45. DOI： 10.16081/j.issn.1006-6047.2018.10.007.

摘要

压水堆核电机组动态模型中参数的稳定性和正确性对保证系统的暂态稳定具有重要意义

因此需要设计合适的模型参数评价方法。针对压水堆核电机组动态模型

按照内部物理边界将其分解为多个子模块模型;根据各子模块的微分方程数学模型推导

基于变量偏差的传递函数定性评价参数的改变对各子模块输出变量稳态值的影响;基于参数灵敏度的终值是否为零值和灵敏度指标大小的判定

合理选择参数的获取方案以提高参数获取效率及准确性。采用基于群体最优值摄动的粒子群优化算法获取模型参数

算例结果验证了所提参数评价方法的有效性。

Abstract

The stability and correctness of the parameters in the dynamic model of PWR（ Pressurized Water Reactor）nuclear power unit are of great significance to ensure the transient stability of the system

so it is necessary to design a suitable parameter evaluation method. The dynamic model of PWR nuclear power unit is divided into multiple submodule models according to its internal physical boundaries. According to the derivation for the differential equation mathematical model of each sub-module

the influence of the parameter variation on the steady-state output variables of each sub-module are estimated qualitatively based on the transfer function of variable deviation. In order to improve the efficiency and accuracy of parameter obtainment

a reasonable parameter acquisition scheme is chosen based on the determination of the sensitivity index value and whether the final value of the parameter sensitivity is zero. Particle swarm optimization algorithm based on the perturbation of the group optimal value is applied to obtain the model parameters

and the results of the example verify the effectiveness of the proposed parameter evaluation method.

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