电力系统自动化2025，Vol.49Issue(9)：157-165,9.DOI:10.7500/AEPS20240426007
基于改进容积卡尔曼滤波的含光伏配电网动态状态估计
Dynamic State Estimation for Distribution Network with Photovoltaic Based on Improved Cubature Kalman Filter
摘要
Abstract
State estimation provides data support for the secure and stable operation of distribution networks with distributed photovoltaic.However,the large-scale integration of distributed photovoltaic has exacerbated the uncertainty of state variables in distribution networks,making it challenging for traditional static state estimation of distribution networks to rapidly track the dynamic changes of state variables.In this paper,a dynamic state estimation method for distribution networks with photovoltaic based on the improved cubature Kalman filter is proposed.This method establishes a dynamic state estimation model for distribution networks with distributed photovoltaic,treating the electrical variables on the photovoltaic side as the state variables to be estimated.An adaptive cubature Kalman filter algorithm based on singular value decomposition is proposed,where singular value decomposition is replaced with Cholesky decomposition and realizes adaptive filtering to modify the process noise parameters in real time,resolving the issues of filtering interruption or divergence caused by the non-positive definiteness of the covariance matrix in the traditional cubature Kalman filter.The simulation results show that the proposed method can ensure high state estimation accuracy in the case of stable operation or sudden changes in state variables of the photovoltaic integration system,especially with significant advantages when the photovoltaic output fluctuates.关键词
配电网/光伏/动态状态估计/容积卡尔曼滤波/奇异值分解Key words
distribution network/photovoltaic/dynamic state estimation/cubature Kalman filter/singular value decomposition引用本文复制引用
刘灏,王紫薇,毕天姝..基于改进容积卡尔曼滤波的含光伏配电网动态状态估计[J].电力系统自动化,2025,49(9):157-165,9.基金项目
国家自然科学基金资助项目(52377098). This work is supported by National Natural Science Foundation of China(No.52377098). （52377098）
