Due to a growing energy demand in the Netherlands, efficiently managing electricity distribution is becoming increasingly critical. To mitigate the risk of grid congestion during certain hours, Transmission System Operators (TSOs) and Distribution System Operators (DSOs) are imposing capacity constraints. In a case study we examined how dynamic group limits within energy hubs can help balance electricity distribution and relieve congestion during peak periods.
Despite significant investment in grid expansion, Dutch DSO Stedin has called for reduced electricity consumption during peak hours (read more about this here). One strategy to achieve this is the introduction of dynamic group limits, where companies face restrictions on electricity usage during peak times. In return, they are offered increased capacity during off-peak hours as compensation.
Mathematical modelling for validation
To assess the feasibility of this strategy, we used our Energy Hub Design model, that we developed for our clients to support the design and optimisation of energy hubs. The goal was to determine whether dynamic group limits could improve energy usage within a Dutch business park and yield benefits for all stakeholders.
We focused on dynamically adjusting capacity limits during peak hours (16:00 to 20:00) and expanding them during off-peak hours (00:00 and 06:00). Simulations were conducted at 15-minute intervals, exploring various group limits.
Key findings
- With significant reductions in capacity, the system continued to operate within capacity limits the vast majority of the time. This indicates that dynamic group limits can be effective during most periods of the year and may therefore offer a viable strategy to mitigate the risk of grid congestion.
- Some periods, especially at the beginning and end of the year, posed a higher risk of shortages, even without applying group limits. This is primarily due to a combination of limited renewable energy availability and increased demand during these dark and cold months.
- In all considered scenarios, the increased capacity during off-peak hours did not compensate for the reduced capacity during peak hours. This reflects a broader trade-off: while additional generation during low-demand periods may be cheaper, it is not sustainable. Storage solutions, though more costly, offer a more sustainable and reliable way to address these peak-time constraints.
Potential solutions
To mitigate the risk of shortages resulting from dynamic limits, two main solutions were identified:
- Expanding storage or generator capacity: While the need for additional battery storage varies significantly depending on the group limit percentage, the required extra generator capacity remains relatively constant. However, these investments can be considerable, particularly given that the extra capacity is only needed for short periods of time. Consequently, the costs may outweigh the benefits, making such solutions difficult to justify.
- Flexible peak consumption: By shifting electricity demand away from peak hours, something that can be effectively modelled using the Energy Hub Design model, the examined energy hub can maintain a 15% dynamic limit without reducing the overall consumption or investing in additional storage or generation capacity. Our analysis showed that by making just one company 30% more flexible in its peak consumption (i.e. maintaining at least 70% of its baseline usage), the 15% group limit could be met successfully.
Conclusion
Dynamic group limits present a promising approach to managing capacity constraints in electricity distribution, especially when paired with flexible consumption strategies or targeted investments in energy storage. Our Energy Hub Design model proved to be instrumental in validating these strategies, offering DSOs and businesses in energy hubs a data-driven and mathematical approach to managing evolving energy demands effectively.
To learn more about our Energy Hub Design model or other models to solve congestion issues in the energy market, don’t hesitate to contact us at info@doingthemath.nl.