Developing Synthetic Distribution Models Using Open-Source Data Sets

Research output: NRELPoster


The deployment of distributed generation resources at scale with the distribution side of the power system network over the last two decades has spurred a lot of research interest in distribution networks. Given, the sensitive nature of power system data sets, utilities are still reluctant to open-source distribution networks. Although some open-source data sets are available, they may not cover the region of interest. In this paper, we introduce the Synthetic dIstribution Network Generator (SING), new software that allows users to develop synthetic distribution models, using open-source data sets, in any region of interest within the continental US.
Original languageAmerican English
StatePublished - 2023

Publication series

NamePresented at the 2023 IEEE Power & Energy Society General Meeting, 16-20 July 2023, Orlando, Florida

NREL Publication Number

  • NREL/PO-6A40-86846


  • data set
  • OpenDSS
  • synthetic distribution model


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