中国电机工程学报2025，Vol.45Issue(11)：4336-4350,15.DOI:10.13334/j.0258-8013.pcsee.232509
面向发电机进相深度极限与安全边界量化分析的数字孪生模型
A Digital Twin Model for Quantitative Analysis of the Depth Limit and Safety Boundary of Generator Leading Phase Operation
摘要
Abstract
Generator phase-leading operation serves as a critical solution for addressing reactive power surplus in large-scale grid systems.Prior to grid connection,generators must undergo rigorous phase-leading capability testing.However,the inability to precisely quantify safety boundaries and predict operational risks has frequently led to experimental failures and field accidents during phase-leading operations.Leveraging the high-fidelity and interoperability features of digital twin technology,this study proposes a hybrid mechanistic-data approach to establish a digital twin framework for phase-leading depth limitation and safety boundary quantification,effectively resolving the inherent conflict between modeling precision and practical application requirements.This method constructs a twin mathematical model through the operation mechanism and limiting factors of the phase leading,and then uses the particle swarm optimization algorithm to achieve self-calibration of model parameters based on real-time measurement data.Finally,it achieves quantitative prediction of various safety boundary distances before high-risk deep phase leading.The real-time analysis platform is developed and applied to the grid connection test of two nuclear power units.The results show that the calculation time of the platform is less than 1 minute,and the error of working condition prediction and boundary analysis is not more than 0.8％.The system meets the real-time and accuracy requirements on site,and it can provide safety assurance for power production and operation.关键词
数字孪生/进相深度极限/安全边界/混合驱动/工况预测Key words
digital twin/phase leading limit depth/safety boundary/hybrid drive/working condition prediction分类
信息技术与安全科学引用本文复制引用
王泽民,郝亮亮,鲁秦怡,赵岩,何俊,涂水员..面向发电机进相深度极限与安全边界量化分析的数字孪生模型[J].中国电机工程学报,2025,45(11):4336-4350,15.基金项目
中央高校基本科研业务费专项资助项目(2024YJS051) （2024YJS051）
中广核集团公司科技项目(E23GY00050).The Fundamental Research Funds for the Central Universities(2024YJS051) （E23GY00050）
Scientific and Technological Project of China General Nuclear Power Group Co.(E23GY00050). （E23GY00050）
