分布式能源2024，Vol.9Issue(4)：43-50,8.DOI:10.16513/j.2096-2185.DE.2409405
基于自适应H∞容积卡尔曼滤波的配电网动态状态估计方法
Dynamic State Estimation Method of Distribution Network Based on Adaptive H∞ Cubature Kalman Filter
摘要
Abstract
Due to the random variation of load,the participation of demand response,the fluctuation of distributed power supply,and the variety of measurement devices,the measurement data of distribution network is prone to abnormal values,which leads to the decline of dynamic state estimation accuracy.In order to improve the accuracy of distribution network state estimation,this paper proposed a dynamic state estimation method for distribution network based on adaptive H∞ cubature Kalman filter.Firstly,based on the cubature Kalman filter,the adaptive factor and H∞ filter were combined to deal with and limit the model error.Secondly,combined with the noise estimator,the parameters in the process noise were estimated online to reduce the influence of noise on the prediction error.Finally,a typical distribution network system with 69 nodes was simulated.The simulation results show that the estimation accuracy of the proposed method is improved by more than 10%under three scenarios:system normal operation,demand response participating in peak load shaving and load mutation,maintaining a relatively high estimation accuracy.关键词
状态估计/容积卡尔曼滤波/H∞滤波器/噪声估值器/需求响应Key words
state estimation/cubature Kalman filter/H∞ filter/noise statistic estimator/demand response分类
能源科技引用本文复制引用
粟子聪,廉政..基于自适应H∞容积卡尔曼滤波的配电网动态状态估计方法[J].分布式能源,2024,9(4):43-50,8.基金项目
国家自然科学基金项目(51967004) This work is supported by National Natural Science Foundation of China(51967004) （51967004）
