%0 Journal Article
%T 智能优化算法在核电厂运行数字孪生系统自动调试中的应用研究<br>Application Research on Intelligent Optimization Algorithm in the Automatic Finetune of Nuclear Power Plant Digital-Twin System
%A 肖云龙
%A 张弦
%J Nuclear Science and Technology
%P 64-69
%@ 2332-712X
%D 2023
%I Hans Publishing
%R 10.12677/NST.2023.111007
%X 核电厂运行数字孪生系统需要具备和机组指定状态相匹配的能力，这个过程中需要对仿真模型的参数进行调试，这是一个高维度、带约束的优化问题。本文开发了针对数字孪生系统的自动调试引擎AFE，利用差分进化算法对某核电机组二回路蒸汽系统进行自动调试，通过对有初值问题和无初值问题的测试，以及针对优化算法的改进方案研究，证明了智能优化算法能够较好地应对自动调试的需求。<br />
In order to match the specified state of nuclear power plant, the parameters of the simulation mod-el need to be finetuned. This is a high-dimensional, restrained optimization problem. In this paper, an automatic finetune engine (AFE) is developed for the digital twin system. Differential evolution algorithm is used to finetune the secondary loop steam system. By testing the problems with and without initial value, and studying the improvement of the optimization algorithm, it is proved that the intelligent optimization algorithm can meet the needs of automatic finetune.
%K 数字孪生，核电，差分进化<br>Digital-Twin
%K Nuclear Power
%K Differential Evolution
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=60695