Dispatch Model

The dispatch model estimates the revenue a BESS asset could earn in the market environment forecasted by the production-cost model.

We use an optimization model to simulate the optimal dispatch of a revenue-maximizing storage asset that is free to participate in real-time energy and the five ancillary service markets, subject to realistic constraints.

For each 24-hour period to 2050, the model chooses the optimal schedule of charging and discharging in 15-minute intervals and the optimal hourly ancillary service commitments.

The model outputs one key item:

• An Excel file showing the model run's configuration as well as monthly and yearly summary statistics like average cycles, average real-time energy price and revenue, average ancillary service price and revenue, and total revenue.

Key assumptions

• Perfect foresight - The model optimizes across a 24-hour period, and it 'sees' all energy and ancillary prices during that period. This foresight allows the model to earn more revenue than a real operator, who must act without knowing future prices. We mitigate this effect through realistic constraints.
• Price taker - The model accepts prices as given and its actions have no impact on market prices or outcomes.

What can I use this for?

The model aims to realistically simulate the revenue a battery could earn in given market conditions. Combined with the production cost model, which forecasts prices under different macro scenarios, the dispatch model forecasts BESS revenue. This revenue forecast can be used for financial modeling, thesis building, etc.