Topology Identification for Island Electric Power Systems Through Voltage Curves Similarity and Impedance-Based Distance

The island electric power systems composed of low-voltage distribution networks are becoming increasingly common. However, their topology is often subject to changes due to factors such as distribution network configuration and demand-side management, making it difficult to obtain real-time and accurate topology information. Therefore, this paper presents a novel data-driven approach for identifying the topology of distribution networks using smart meter data. Firstly, the voltage curves similarity (VCS) between nodes is evaluated using discrete wavelet transform, and the impedance-based distances (IBDs) matrix is derived through regression analysis. Secondly, for a given node, its potential upstream nodes (PUNs) are identified by calculating cumulative IBDs to the corresponding nodes and VCS filtering in relation to the root node. Next, further filtering based on the VCS enables selection of the candidate parent nodes (CPNs) from the PUNs. Lastly, when establishing the node connection, the precise parent node is identified from the CPNs using the IBDs between nodes. Utilizing these parent-child node relationships, the topology can be identified by recursively traversing from the root node through the child nodes. Case studies are constructed on the IEEE standard bus system, and the results demonstrate that the proposed method has advantages in terms of accuracy and robustness compared with the benchmark method.