TLDR; Our optimisation algorithm respects all the rules it should.

Including all the physics of batteries, ramp rates, throughput, costs of delivery etc for a battery doing Dynamic Frequency Response.

We assume perfect foresight of prices - but correct this using a real-world calibration, with the help of the Modo Benchmark.

Here's the detail

• By default, we assume a 88% efficiency rate (i.e. a 200MWh system needs 227MWh to charge fully) - but this can be specified in the model.
• Total contracted power (or availability) across the different markets is less than or equal to maximum charge and discharge limits.
• Since the launch of the Enduring Auction Capability (EAC), batteries can provide availability to different dynamic frequency response markets, at the same time. For example, Dynamic Containment High and Regulation Low can be combined.
• We consider how many batteries are participating in each of the dynamic frequency response markets, and the total size of that market. This limits the average accepted volumes (see below on 'Frequency Response Market Saturation limits battery revenues').
• We respect the service delivery rules in Dynamic Frequency Response, as described by the Electricity System Operator in Great Britain:
  • Frequency response contracts are of EFA block duration (and their volume is constant in each EFA block, or 4-hour period).
  • The battery's energy is kept within the allowed state of charge range, as per the rules of each service. This means keeping enough headroom (or footroom) in energy to provide the contracted response at maximum volume for its maximum continuous time (see table below). For example, a battery providing 1 MW Dynamic Regulation High must be able to import 1 MW continuously for up to 1 hour, at all times it is contracted in DRH.
  • For symmetrical frequency response (High and Low), contracted volume is reduced according to that service's de-rating factor (see table below).
  • Batteries participating in frequency response must respect ramp rates. We can't ramp at a rate greater than 5% of the contracted volume in the opposite direction.
    • This means a battery providing 1 MW DRH (high leads to charging) can increase its export power (ie discharge) by 0.05 MW per minute.
• We model the throughput in each response service (see table below).

• We assume perfect foresight of prices, but then calibrate based on battery Benchmark data to make revenues readily usable in a business case.