Accelerating e-mobility charging integration with dynamic grid capacity management

The evolving landscape of distributed energy resources (DER), which need to be integrated mainly in low-voltage (LV) grids, increases the demand for measures such as dynamic grid capacity management. Traditional grid capacity planning, based on fixed assumptions, often fails to accommodate modern energy consumption patterns and local generation variability. This study, within the Aspern Smart City Research context, explores dynamic grid capacity management using operating envelopes (OEs). We compare dynamic capacity management with a static, data-driven approach and conventional pattern-based planning. Advanced approaches allow for day-ahead and real-time adjustments based on current grid conditions, ensuring optimal capacity utilization. Using a practical example from Vienna, we evaluate the enforceability of OEs in urban LV networks. We model a representative subnetwork in the BIFROST simulation environment to enhance flexibility sources and run comparable simulations for KPI calculations. The hosting capacity for additional EV charging facilities is used as a KPI to compare static and dynamic approaches against a reference scenario. Our findings suggest that dynamic grid capacity management enhances grid efficiency and utilization, offering significant advantages by rethinking safety margins. Insights from this study will inform future planning rules and regulations for a more resilient and adaptable grid infrastructure.