基于有向邻接矩阵的配电网拓扑检测与识别

准确的拓扑结构是配电网精细化管理和安全运行的基础。针对现有配电网拓扑识别方法无法确定网络潮流方向以及拓扑变动检测方法受负荷突变影响大的问题,提出一种基于有向邻接矩阵的配电网拓扑变动检测与识别方法。首先,提出一种基于有向邻接矩阵的配电网拓扑识别模型,将配电网的未知拓扑描述为不确定的有向邻接矩阵,实现配电网的拓扑识别并确定潮流方向。其次,提出一种基于节点电压邻接矩阵的拓扑变动检测方法,通过分析相邻节点电压幅值的下降趋势判断拓扑是否发生变动。此外,所提出的拓扑变动检测方法可以缩小未知拓扑的范围,降低拓扑识别问题的变量规模。最后,通过仿真分析验证了所提方法的正确性和有效性。

Distribution network topology detection and identification based on a directed adjacency matrix

Accurate topology is the basis for good management and safe operation of a distribution network. There are problems in that the existing distribution network topology identification methods cannot determine the direction of the network power flow and the topology change detection method is greatly affected by load mutations. This paper proposes a distribution network topology change detection and identification method based on a directed adjacency matrix. First, a distribution network topology identification model based on a directed adjacency matrix is proposed. The model describes the unknown topology of the distribution network as an uncertain directed adjacency matrix to realize the topology identification of the distribution network and determine the power flow direction. Secondly, a topology change detection method based on a node voltage adjacency matrix is proposed. This method judges whether the topology has changed by analyzing the downward trend of the voltage amplitude of adjacent nodes. In addition, the method proposed can narrow the scope of unknown topology and reduce the variable scale of the topology recognition problem. Finally, simulation analysis verifies the correctness and effectiveness of the proposed method. This work is supported by the National Natural Science Foundation of China (No. 51907114).