Synthetic Distribution Grid Generation Based on High Resolution Spatial Data

Abstract

Realistic distribution grid models are essential for the analysis and the evaluation of novel concepts needed for a consequent energy transition. Detailed models of actual power systems are often not available due to security concerns and confidentiality restrictions. In this paper, we propose a grid synthetization procedure based on high resolution spatial datasets released by Dutch Distribution System Operators. We manage to generate calculable radial networks and identify transformers. Subsequently, we dimension all asset types based on a heuristic approach and synthetic peak loads which we derive from the Dutch land register dataset and available statistics. The results are validated based on Complex Network Science and show a high statistical conformity with available data of actual distribution grids.