@article{Mao2024, 
author = {Mingming Mao and Zaijun Wu and Dongliang Xu and Junjun Xu and Qinran Hu},
title = {Community-detection-based Approaches for Distribution Network Partition},
year = {2024},
journal = {CSEE Journal of Power and Energy Systems},
volume = {10},
number = {5},
pages = {1965-1976},
keywords = {Community detection, distribution network partition, three-phase imbalance},
url = {https://www.sciopen.com/article/10.17775/CSEEJPES.2020.04150},
doi = {10.17775/CSEEJPES.2020.04150},
abstract = {A rational partition is the key prerequisite for the application of distributed algorithms in distribution networks. This paper proposes community-detection-based approaches to a distribution network partition, including a non-overlapping partition and a border-node partitioning method. First, a novel electrical distance is defined to quantify the coupling relationships between buses and it is further used as the edge weight in a transformed equivalent graph. Then, a vertex/link partition community detection approach is applied to over-partition the network into high intra-cohesive and low inter-coupled subregions. Following this, a greedy algorithm and a tabu search method are combined to merge these subregions into target numbers according to the scale similarity principle. The proposed approaches take the influence of three-phase imbalance into consideration and they are decoupled from the power flow. Finally, the approaches are tested on an IEEE 123-bus distribution system and the results verify the effectiveness and the credibility of our proposed methods.}
}