Making Our Power Grid Sweat – Daniël Kok & Anna Van Velsen, Alliander
Event Recap: LF Energy Summit Europe 2025
TL;DR
At LF Energy Summit Europe 2025, Daniël Kok and Anna Van Velsen of Alliander presented how thermal models can help utilities move from static asset limits toward cyclic or dynamic ratings. The session explored how transformer temperature modeling can identify residual grid capacity, improve grid utilization, and support collaboration between DSOs through open source software.
Why Grid Congestion Requires Better Asset Utilization
Van Velsen opened by describing her work as a data scientist at Alliander, where she helps asset managers move from continuous or static limits toward cyclic or dynamic ratings of assets. The team has been developing thermal models to identify new operating limits and better understand how existing infrastructure can be utilized.
The presentation framed this work against growing grid congestion challenges in the Netherlands. Van Velsen described long waiting lists for grid connections, rising costs, and solutions that are not yet sufficient to meet demand.
Alongside grid expansion projects such as new substations, transformers, and cables, Alliander is also focused on improving utilization of the existing grid. That means increasing the amount of power flowing through current infrastructure while staying within acceptable thermal and aging limits.
Using Thermal Models to Understand Asset Limits
The speakers explained that assets including transformers, bare conductors, switchgear, and cables are constrained not only by load limits, but also by thermal limits. Although sections of the grid may appear full based on static ratings, measured transformer oil temperatures showed that some assets were still operating well below their thermal thresholds.
According to Van Velsen, understanding asset temperature is essential for determining both utilization levels and accelerated aging. Because installing sensors across every transformer, cable, and switchgear unit would be expensive and time consuming, Alliander instead uses thermal models to estimate asset temperatures and identify remaining thermal capacity.
Kok explained that the team focused primarily on transformers, which are often the limiting assets in substations. Alliander’s transformer thermal model builds on an existing IEC transformer thermal model and calculates values including hotspot temperature and top oil temperature using transformer load profiles, transformer specifications, and ambient temperature data.
The model has been developed and validated over the past one and a half years using measurements from Alliander’s own power grid.
From Static Limits to Cyclic Ratings
The session described thermal modeling as a way to move from static limits toward cyclic limits. The approach involves calculating transformer temperatures under current load conditions, increasing loading where acceptable, and repeating the process until the transformer reaches an acceptable operating range.
Using this approach, Alliander evaluated critical areas across its substations and identified approximately 600 MVA of additional potential capacity through thermal modeling. Kok compared that figure to roughly 100,000 households at a lower estimate, or up to 200,000 households under a more optimistic estimate.
The speakers emphasized that thermal modeling allows utilities to better understand risk while improving utilization of existing infrastructure before major physical grid expansion projects are completed.
Open Source Collaboration Across DSOs
Van Velsen explained that the decision to open source the thermal model came after discussions with data scientists from other distribution system operators who were interested in the work but unable to access the software.
Kok said Alliander open sourced the model several months before the presentation. Since then, the team has organized workshops for developers and asset managers, shared transformer data to improve validation efforts, and received contributions from another DSO.
The speakers also described ongoing discussions with a transmission system operator about features needed for broader adoption. They emphasized that congestion challenges are affecting multiple DSOs across the Netherlands and that collaboration through open source development can help utilities improve thermal modeling capabilities together.
About LF Energy
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Learn more: https://lfenergy.org
Last updated: May 21, 2026
AI Disclosure
This post used artificial intelligence tools for research, structural assistance, or grammatical refinement. The final content was reviewed, edited, and validated by human contributors to LF Energy to ensure accuracy and alignment with our community standards. We remain committed to transparency in the use of generative technologies within the open source ecosystem.
