Cluster-and-Connect: An algorithmic approach to generating synthetic electric power network graphs

Generating synthetic network graphs that capture key topological and electrical characteristics of real-world electric power systems is important in aiding widespread and accurate analysis of these systems. Classical statistical models of graphs, such as small-world networks or Erdös-Renyi graphs, are unable to generate synthetic graphs that accurately represent the topology of real electric power networks - they do not appropriately capture the highly dense local connectivity and clustering as well as sparse long-haul links observed in electric network graphs. This paper presents a model that parametrizes these unique topological properties of electrical power networks and introduces a new Cluster-and-Connect algorithm to generate synthetic networks using these parameters. Using a uniform set of metrics proposed in the literature, the accuracy of the proposed model is evaluated by comparing the synthetic models generated for specific real electric network graphs.