GeoDistNet: An Open-Source Tool for Synthetic Distribution Network Generation

TL;DR

GeoDistNet is an open-source tool that generates realistic, geographically interpretable synthetic distribution networks from public GIS data, aiding studies where detailed utility data is inaccessible.

Contribution

It introduces a reproducible workflow for creating simulation-ready distribution feeders from publicly available geographic information.

Findings

Generated feeders are geographically interpretable and topologically structured.

The tool produces models compatible with pandapower for various loading levels.

Case study demonstrates practical applicability in real urban settings.

Abstract

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.