Applied Energy Journal: Demand curtailment allocation in interconnected electricity markets
In this published, peer reviewed paper for the prestigious Applied Energy Journal, the authors* at TransnetBW, the German TSO, have developed a framework and mechanism to evaluate the spatial and temporal fairness (employing the Gini index) of demand curtailment and then used BID3 modelling to investigate the studied methods
The team has started with the observation that resource adequacy assessments should account for cross-zonal and intertemporal dependencies, especially considering today’s electricity systems with high levels of intermittent renewable generation. Therefore, a fair and consistent allocation of unavoidable demand curtailment across different regions and time periods is needed. The team sees that without such a mechanism, conventional resource adequacy metrics—such as the Loss of Load Expectation (LOLE) and Expected Energy Not Supplied (EENS)—lose their relevance at the national level, making them random and less effective.
Accordingly, the team has developed a framework for evaluating the spatial and temporal fairness of demand curtailment allocation. Subsequently, they have introduced two model formulations – a linearized approach and a post-processing approach – that allow to implement a demand curtailment allocation mechanism into dispatch modelling.
The study’s results from all of Europe simulations show that on an overall system level both approaches substantially increased the spatial fairness of the demand curtailment allocation with no major increases of the total EENS across all zones. Nevertheless, team notes that linearized approach achieves a fairer temporal allocation across different time steps.
Example results for Germany show string effects of the proposed approaches in a curtailment sharing in this single individual zone. It shows that for the German example, LOLE varying between 12 and 116 hours per year and EENS between 94.9 and 293.2 GWh/year depending on the simulation set up.
*Authors (the team):
- Christoph Fraunholz
- Ali Tash
- Heike Scheben
- Alexander Zillich
