Summary
The integration of heat pumps and electric vehicles into low-voltage networks creates increasing reinforcement needs in future high-electrification scenarios. Distribution network reconfiguration can redistribute load flows to reduce these costs. Existing methods focus on operational loss minimisation, use static load models, and lack validation on large-scale lowvoltage networks. This paper presents a memetic algorithm to minimise reinforcement costs through optimised topology as input for subsequent automated network planning. The method combines a reinforcement-oriented objective aligned with discrete equipment ratings, topologyadaptive coincidence factors recalculated for each configuration, and a scalable island-based algorithm architecture.
Read more Read lessApplication to a municipal network area with 43 secondary substations and 564 optimisable switches under a 2045 scenario shows 18.3% reinforcement cost reduction compared to 7.9% for traditional loss-based methods. One-time reinforcement investment costs for the 2045 planning horizon decrease by approximately 490,000 Euro compared to the unoptimised baseline.
Additional informations
| Publication type | Session Materials |
|---|---|
| Reference | C6_12409_2026 |
| Publication year | |
| Publisher | CIGRE |
| Country | Germany |
| Study committees | |
| File size | 641 KB |
| Price for non member | 30 € |
| Price for member | 30 € |
Authors
REBENTISCH Tobias - University of Wuppertal Germany; BECKER Christoph - University of Wuppertal Germany; RIEDLINGER Tobias - University of Wuppertal Germany; TALMOND Felix - University of Wuppertal Germany; ZDRALLEK Markus - University of Wuppertal Germany; KERZEL Marco - Stadtwerke Hilden GmbH Germany; HEUBERGER Daniel - Stadtwerke Hilden GmbH Germany
