How do we use our dispatch model?
In our most recent Signal update, we provide a forward view of asset-specific revenues in a combination of wholesale and Dynamic Containment. We push our hourly forward power curve through a dispatch model to determine optimized revenues for different battery parameters and strategies.
This article gives an overview of our modeling assumptions and how we calculate revenues.
Assumptions
We calculate revenues in wholesale and Dynamic Containment by making several assumptions about the battery we’re modeling and its bidding strategies:
During EFA blocks when a battery provides Dynamic Containment, it does not participate in wholesale.
We model symmetrical Dynamic Containment (e.g. provision of both High and Low services) with a de-rating factor of 0.9. We assume that a battery either provides both services symmetrically with no wholesale trading. Or it does not provide either service and trades in wholesale.
We set the battery state-of-charge in line with Dynamic Containment delivery requirements. It must have sufficient capacity to charge and discharge at its maximum power for 15 minutes when it provides the service. Figure 6, below, shows an example of this. The battery maintains 25 MWh (100 MW x 0.25 h) of headroom while providing Dynamic Containment.
The round-trip efficiency of the battery is 88%. To fully charge a 100 MWh battery, we must purchase 100 MWh/88% = 114 MWh. For a 1-hour duration battery (100 MW), charging must be done over two hour-long periods. Firstly, purchasing 100 MWh in the cheapest hour and then 14 MWh in the second cheapest hour.
We do not model the throughput of the battery while providing Dynamic Containment. If the battery is a BM unit, any imbalance charges will be settled through ABSVD payments. We do not model any state-of-charge management for Dynamic Containment.
Modeling revenues
We input the above assumptions, forward power prices, and battery parameters (duration, cycling, EFAs for Dynamic Containment delivery) into the dispatch model. The model optimizes the wholesale trading strategy around Dynamic Containment provision to maximize revenue. We show an example day in the figure below.
We use the output of the dispatch model and forward power prices to calculate wholesale revenues for different input scenarios. We calculate Dynamic Containment revenues using the forward High and Low prices and applying the symmetrical de-rating factor of 0.9.