基于节点度搜索分区的配电网状态估计方法

State estimation method for distribution networks based on node degree search partitioning

随着配电网规模的扩大,传统集中式状态估计算法所需构建模型日趋复杂,导致求解过程计算量增大,状态估计时效性和准确性下降。针对此问题,提出一种基于节点度搜索分区的配电网状态估计方法。构建多种区域划分方法,在保证划分后系统可观的前提下对比不同划分方式状态估计的精度与时长,并进一步分析量测冗余度对状态估计准确性的影响,选取IEEE 30节点配电系统进行仿真分析,仿真结果表明所提分布式状态估计方法在状态估计速度、精度上具有明显优势。

With the expansion of the distribution network scale,the traditional centralized state estimation algorithms require increasingly complex model construction,leading to increased computational complexity during the solution process,reduced timeliness and accuracy of the state estimation.Aiming at this problem,a distribution network state estimation method based on node degree search partitioning is proposed.Firstly,a node degree search partitioning method based on balanced regions is proposed,and the measurement model and distributed state estimation model for the distribution network are designed.Secondly,the distributed state estimation model is solved in three stages.Finally,the IEEE 30 node distribution system is selected for simulation analysis.While ensuring the observability of the system after partitioning,a comparison is made among different partitioning methods in terms of the accuracy and duration of state estimation.The impact of measurement redundancy on state estimation accuracy is further analyzed.The simulation results demonstrate that the proposed distributed state estimation method has significant advantages in terms of state estimation speed and accuracy.