Topological characterization and modeling of dynamic evolving power distribution networks

Existing complex network models are either with unvaried network size or based on simple growth mechanisms which cannot accurately describe the operational dynamics and characteristics of realistic networks. In this paper, we exploit the dynamic evolving phenomenon of power distribution networks covering its growth, reconnection and shrinking characteristics from the network topology perspective, and attempt to produce a novel dynamic evolving model through introducing the locating probability and shrinking mechanism. The proposed modeling approach is assessed and validated through extensive numerical simulation experiments for a range of standard IEEE power test systems. The statistical results reveal that the node degree distribution of the power network follows the power-law distribution and the node removal probability of the network dynamic has a significant impact on the network evolvement and robustness. Such macroscopic topological findings can greatly benefit the power distribution network operators (DNOs) from many aspects, including network planning, vulnerability analysis, fault prediction and cost-effective reinforcement.

► We proposed a statistical dynamic evolving model of power distribution networks from the topological aspect. ► The proposed topological dynamic evolving model firstly considered the shrinking mechanisms. ► The impact of the shrinking mechanism to the power network evolution was investigated and analyzed. ► The proposed dynamic model is validated by the use of standard IEEE test power scenarios.