GeoDistNet: An Open-Source Tool for Synthetic Distribution Network Generation
This tool addresses the need for realistic distribution network models for researchers and engineers when detailed utility data is unavailable, though it is incremental as it builds on existing methods for network synthesis.
The authors tackled the lack of accessible and geographically realistic distribution network models by developing GeoDistNet, an open-source tool that generates synthetic networks from public geographic data, resulting in a case study in Melbourne that produced a feeder usable in power-flow analysis under multiple loading levels.
Distribution-level studies increasingly require feeder models that are both electrically usable and structurally representative of practical service areas. However, detailed utility feeder data are rarely accessible, while benchmark systems often fail to capture the geographic organization of real urban and suburban networks. This paper presents GeoDistNet, an open-source tool for synthetic distribution network generation from publicly available geographic information. Starting from map-derived spatial data, the proposed workflow constructs a candidate graph, synthesizes feeder-compatible radial topology through a mixed-integer formulation, assigns representative electrical parameters and loads, and exports the resulting network for power-flow analysis. A Melbourne case study shows that the generated feeder remains geographically interpretable, topologically structured, and directly usable in \texttt{pandapower} under multiple loading levels. GeoDistNet therefore provides a reproducible workflow for bridging publicly accessible GIS data and simulation-ready distribution feeder models when detailed utility networks are unavailable.