基于改进广义极大似然估计的配电网状态估计方法

Distribution Network State Estimation Method Based on Improved Generalized Maximum Likelihood Estimation

针对配电网状态估计中不同量测数据的数据成分、数据精度以及刷新频率等方面存在异同,在保证传统状态估计器结构前提下,提出了一种新的估计融合体系,同时将改进广义极大似然(GM)估计和估计融合体系相结合,用以估计系统节点电压幅值和相角。首先,采用GM估计增强估计模型的鲁棒性,通过使用自适应映射统计以及对GM估计中目标函数的权函数进行分析,将改进GM估计法用于状态估计。其次,考虑到传统量测系统与相量量测系统在测量通道以及仪表采样速率方面技术不同,在传统状态估计器的基础上充分利用相量量测数据对不同的估计模块进行状态估计。同时,利用多传感器数据融合理论(MDF)对估计结果进行融合处理,从而得到最优估计值。最后,改进的IEEE 14与IEEE 33节点配电网算例的仿真分析,验证了所提改进GM估计和估计融合体系的有效性和可靠性。

In view of the similarities and differences in data composition,data accuracy and refresh frequency of different measurement data in distribution network state estimation,a new estimation fusion system is proposed on the premise of ensuring the structure of the traditional state estimator.At the same time,the improved generalized maximum likelihood(GM)estimation and estimation fusion system are combined to estimate the system node voltage amplitude and phase angle.Firstly,GM estimation is used to enhance the robustness of the estimation model.By using adaptive project statistics and analyzing the weight function of the objective function in GM estimation,the improved GM estimation method is applied to the state estimation.Secondly,considering that the traditional measurement system is different from the phasor measurement system in terms of measurement channel and instrument sampling rate,based on the traditional state estimator,the phasor measurement data is fully utilized to estimate the state of different estimation modules.At the same time,the multi-sensor data fusion theory(MDF)is used to fuse the estimated results to obtain the optimal estimation value.Finally,the simulative analysis on the improved IEEE 14 and IEEE 33-bus distribution network examples verifies the validity and reliability of the improved GM estimation and estimation fusion system.