Abstract
In scientific research, the debate on open data is still evolving. The development of open-source benchmark data set is essential to the entire community as it enables empirical analysis of developed algorithms, speedy development of novel solutions, and strategies for solving real problems. In this paper, we presented a hybrid approach based on OpenStreetMap (OSM) and Python integration to generate an open-source dataset for power distribution networks. Using Overpass Query Language, multiple queries are constructed to collect the different features of distribution networks such as power line segments, transformers, poles, end consumers (households), and substation locations. The queried data is further accessed and downloaded with the Overpass API in Python. The validation of concept is provided with a case study of small region in Australia and results are illustrated with geographical visualizations. The results show that developed datasets are effective as it supports the geographical validation of realistic distribution network models.