Forecasting optimal running profiles for behind the meter batteries

How we helped an industrial client assess the value of installing a battery energy storage system at one of its sites taking account of onsite solar generation and demand.

The background

We worked with an industrial client who was considering building a battery storage asset on sites that had existing (or planned) onsite renewable generation and demand load. Locating a battery on an active commercial or industrial site means the asset can allow the site to avoid paying high import power prices (including non-commodity elements), by discharging to supply demand at those times. The asset can then charge at times of low import prices, or make use of any excess renewable generation, using this to charge the battery instead of exporting to the grid at an unfavourable price.

We provided the client with both forecasts of the expected profit over the battery’s lifetime under different strategies and configurations, and licenced a model for in-house client teams to perform their own analysis across multiple sites and scenarios

Our solution

After agreeing market assumptions with the client, LCP’s stochastic dispatch model was then run to obtain granular price forecasts for the next 20-30 years across multiple market scenarios. This pricing data, along with site-specific onsite generation and demand profiles, was then used in our Standalone Battery Optimisation Model. This model allows users to input prices and expected on-site load, and gives an optimal storage profile (using the same algorithm employed in LCP EnVision) and expected net profit for each day considered.

These actions accounted for any opportunities for the asset to charge either from excess onsite generation or from the grid, as well as discharge either to supply onsite demand or export to the grid. Alternative strategies were also considered, such as the asset competing in the frequency response market instead of supplying onsite demand.

The outcome

Our analysis was used to inform decisions around onsite battery assets, including the operating strategy and asset configuration. Also, LCP’s standalone battery optimisation model was licensed to allow the client to perform their own analysis on a range of other potential sites and configurations.