Cluster Partitioning Method for Honeycomb Distribution Networks Based on the Improved Newman Algorithm

With the integration of large-scale distributed power sources into honeycomb distribution network (HDN), which causes the challenges of increased uncertainty in output power, we propose a cluster partitioning strategy. It's based on the improved Newman algorithm for HDN clustering. Firstly, the topological structure characteristics of the HDN were analyzed. Secondly, to evaluate the effectiveness of the cluster partitioning, a comprehensive index which includes spatial distance indicator and power balance coefficient indicator for HDN clusters was established to assess the result of the partitioning. Then, proposing a cluster partitioning method based on the improved Newman algorithm. Finally, to validate the effectiveness of the proposed method, a HDN model was selected for simulation. This method could mitigate the randomness of their output power.