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Battery Storage case study

Forecasting a standalone battery asset’s revenue streams

The background

We had been commissioned to provide battery asset forecasts for multiple client projects, including transaction due diligence and in-house strategic analysis. These include forecasts of wholesale and balancing margins, ancillary service revenues, operating profiles and other embedded costs or benefits across a range of market scenarios.

Our solution

Using either in-house assumptions or those agreed with the client, we used LCP’s EnVision to model the future capacity mix of the system under different scenarios and the revenue streams of battery assets under each of these scenarios. The revenue modelling used our stochastic dispatch model to understand the range of revenue streams for the units within each scenario.

The modelling employs a fundamentals driven approach to consider the actions of each unit in each individual period, in both the wholesale and balancing markets. Storage actions are optimised to maximise their profit against these price signals, subject to the unit’s operating constraints and considerations such as imperfect price foresight. This modelling accounts for the impact of a variety of market factors, such as competition from other battery and flexible technology build-out, commodity prices and renewable penetration, as well as the intrinsic technical capabilities of the asset such as duration, efficiency and degradation rates.

As well as wholesale and balancing revenue streams, we provided forecasts for ancillary service revenue from Dynamic Containment and other frequency response products. Our modelling also provided forecasts for locational charges and benefits (such as TNUoS, GDUoS & Triad), and Capacity Market payments (clearing prices and derating factors). In the long term, we anticipate that sufficient levels of competition will mean these revenue streams will be valued based on the opportunity cost of forgoing energy market revenues, subject to any costs in providing the services and benefits from lower levels of degradation in the unit.

Finally, we worked with the client to help them understand the impact of battery degradation and determining operational strategies to resolve the trade-off between higher cycles and revenues and delayed investment for repowering.

The outcome

The results from our forecasts have been used by the client in Great Britain to inform decisions around battery asset investment, including determining the appropriate specification (such as size and duration) of the asset, and an operational strategy to maximise the revenues achievable.

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