arXiv subjects

Benjamin Stöckl

Publications and source records attributed to Benjamin Stöckl.

3 recordsLinked to original sources

arXiv2026

Voltage-Aware Grid Aggregation: Expanding the European High-Voltage Network

Energy system optimization models are indispensable for planning the European energy transition. Yet their applicability is constrained by the fundamental trade-off between spatial detail and computational tractability. Modelers often tackle this by spatially aggregating electricity networks. Existing methods, however, neglect differences in voltage levels, reducing them to a single level and thereby overlooking the critical role of transformers in expansion planning. Therefore, we propose a novel voltage-aware network partitioning and aggregation methodology that preserves individual voltage levels and transformers. We demonstrate the effectiveness of this approach and compare it against a voltage-unaware grid aggregation by solving a network expansion problem for a European case study using PyPSA. Our findings show that the proposed methodology preserves up to 70% of the transformer expansion costs in the aggregated model compared to the full grid model, thereby significantly improving the accuracy of investment decisions for transformers in the aggregated grid.

math.OC↗

arXiv2026

NPAP: Network Partitioning and Aggregation Package for Python

NPAP (Network Partitioning and Aggregation Package) is an open-source Python library for reducing the spatial complexity of network graphs. Built on NetworkX, it provides an accessible standalone package designed to be readily integrated with other software and frameworks. Instead of treating the spatial reduction process as a single action, NPAP explicitly splits it into two distinct steps: partitioning, which assigns vertices (nodes) to groups (clusters), and aggregation, which reduces the network based on a given assignment. NPAP's strategy pattern architecture allows users to employ and register custom partitioning and aggregation strategies seamlessly without modifying the core code. Currently, NPAP provides 13 different partitioning strategies and two pre-defined aggregation profiles. Although initially developed with a focus on power systems, its architecture is general-purpose and applicable to any network graph.

cs.SI↗

arXiv2025

Congestion-Sensitive Grid Aggregation for DC Optimal Power Flow

The vast spatial dimension of modern interconnected electricity grids challenges the tractability of the DC optimal power flow problem. Grid aggregation methods try to overcome this challenge by reducing the number of network elements. Many existing methods use Locational Marginal Prices as a distance metric to cluster nodes. In this paper, we show that prevalent methods adopting this distance metric fail to adequately capture the impact of individual lines when there is more than one line congested. This leads to suboptimal outcomes for the optimization of the aggregated model. To overcome those issues, we propose two methods based on the novel Network Congestion Price metric, which preserves the impact of nodal power injections on individual line congestions. The proposed methods are compared to several existing aggregation methods based on Locational Marginal Prices. We demonstrate all methods on adapted versions of the IEEE RTS 24- and 300-Bus systems. We show that the proposed methods outperform existing approaches both in terms of objective function value error and maximum line limit violation, while exhibiting faster node clustering. We conclude that aggregation methods based on the novel Network Congestion Price metric are better at preserving the essential physical characteristics of the network topology in the grid aggregation process than methods based on Locational Marginal Prices.

math.OC↗