On the Flexibility Potential of a Swiss Distribution Grid: Opportunities and Limitations

TL;DR

This work addresses the challenge of extracting aggregated distribution-grid flexibility in the face of rising distributed energy resources. It introduces a linearized OPF-based $FFOR$ framework to quantify how heat pumps, PV, and BESS contribute to flexibility in the Walenstadt grid, accounting for time-varying conditions and grid topology. The authors show that incorporating small-scale assets can yield flexibility comparable to large-scale storage, but that flexibility is highly time- and topology-dependent, often nonlinearly saturating due to feeder limits. The study provides practical insights for planning Swiss distribution networks, illustrating how device proliferation interacts with network constraints and guiding decisions on reinforcement versus leveraging device-level flexibility. The results emphasize that system-wide flexibility cannot be inferred simply from device counts, highlighting the critical role of grid topology in shaping realized flexibility.

Abstract

The growing integration of distributed renewable generation and the electrification of heating and transportation are rapidly increasing the number of flexible devices within modern distribution grids. Leveraging the aggregated flexibility of these small-scale distributed resources is essential to maintaining future grid-wide stability. This work uses the Swiss distribution grid of Walenstadt as a case study to provide insights into the aggregated flexibility potential of distribution grids. It demonstrates that incorporating devices such as heat pumps and photovoltaic systems significantly enhances distribution grid flexibility. It investigates the time-varying nature of aggregated flexibility and highlights how it can vary seasonally. Furthermore, simulations of future scenarios reveal that aggregated flexibility does not increase linearly or monotonically with higher levels of flexible device penetration. This is primarily due to the overloading of individual feeders, which underscores the impact of grid topology and network constraints on the aggregated flexibility potential.

Figures (9)

• Figure 1: FORs of three individual flexible devices.
• Figure 2: Example of an FFOR at the PCC.
• Figure 3: Walenstadt grid: The nodes represent either connection points for the large BESS (top left) or run-of-river power plants, or represent transformer substations to the LV grid. Controllable loads are represented by triangles, and yellow-colored nodes indicate installed PV capacity in the downstream network.
• Figure 4:
• Figure 5: Illustration of the polynomial relationship between temperature and net active power. Left: Data and polynomial fit for node A, showing a significant regression fit, indicating a moderate amount of heat pump capacity. Right: Data for node C, showing no significant polynomial relationship, indicating no to very little heat pump capacity.