Automated Greenfield-Planning of Optimized Low-Voltage Distribution Networks with Street-Side Differentiation

Planning integrated energy infrastructures, especially in new quarters, poses high complexity, but also significant optimization potential and therefore requires a structured approach for optimization. This paper presents a novel automated method for optimizing low-voltage distribution networks, incorporating street-side differentiation to reflect detailed urban layouts. The method uses a genetic algorithm-based optimization and is validated using an exemplary quarter with publicly available data for a Geographic Information System. The validation demonstrates its ability to create technically feasible and spatially realistic low-voltage networks with reduced manual planning effort. The method enables consistent, scalable application to multiple representative new quarters, supporting the establishment of general cross-sector principles for greenfield planning of integrated energy infrastructures.