电力系统自动化2025，Vol.49Issue(13)：103-112,10.DOI:10.7500/AEPS20240806006
基于MCC-PCKF的跟网型变流器时变虚拟惯量与状态估计
Time-varying Virtual Inertia and State Estimation of Grid-following Converter Based on Maximum Correntropy Criterion and Polynomial Chaos Kalman Filter
摘要
Abstract
In the context of renewable energy integration,the inertia estimation of asynchronous generators is crucial for addressing active power disturbances and ensuring the stable operation of the system.Aiming at the time-varying characteristics of virtual inertia from renewable energy sources,a dynamic inertia and state estimation model for grid-following renewable energy asynchronous generators is established.A polynomial chaos Kalman filter(PCKF)algorithm is used to estimate the inertia parameters and states of the power system.Considering the issues of accuracy and robustness decrease of the PCKF algorithm in the presence of anomalous noise,a new cost function based on the maximum correntropy criterion is introduced to capture higher-order statistics.An estimation method for the time-varying virtual inertia of renewable energy asynchronous generators based on the maximum correntropy criterion and polynomial chaos Kalman filter(MCC-PCKF)is proposed,which effectively improves the robustness and accuracy of the estimation method.To validate the performance of the proposed method,case studies are conducted in the modified IEEE 39-bus system,and comparisons are made with the PCKF method.The results verify the robustness and accuracy of the proposed MCC-PCKF algorithm in time-varying inertia estimation under anomalous noise conditions.关键词
跟网型变流器/虚拟惯量/惯量估计/状态估计/最大熵准则/混沌多项式卡尔曼滤波Key words
grid-following converter/virtual inertia/inertia estimation/state estimation/maximum correntropy criterion(MCC)/polynomial chaos Kalman filter(PCKF)引用本文复制引用
王渝红,王雪珂,文玉玲,郑宗生,廖建权,刘咏玥..基于MCC-PCKF的跟网型变流器时变虚拟惯量与状态估计[J].电力系统自动化,2025,49(13):103-112,10.基金项目
国家重点研发计划资助项目(2021YFB2400800). This work is supported by National Key R&D Program of China(No.2021YFB2400800). （2021YFB2400800）
