ERCOT Battery Benchmark

Our ERCOT Battery Benchmark bridges the gap in the 60-day disclosure data from ERCOT, to provide your team with real-time insight into battery market revenues.

The ERCOT BESS Index is calculated using the asset revenues of all operational battery energy storage assets in ERCOT. This data is calculated based on SCED disclosure data provided by ERCOT 60 days after the delivery date.

To fill this gap, Modo publishes an ERCOT Battery Benchmark "nowcast", a provisional estimate of daily fleet-wide battery revenue based on live market-wide data. This live estimate has a 99.8% correlation and a median absolute daily error of $19/MW with the ERCOT Battery Index. The ERCOT Battery Benchmark is published daily on Modo's Benchmarking overview page, available to Modo subscribers only.

Energy Revenue

Input Data

The datasets we use to calculate the ERCOT Battery Benchmark are all available via the Modo API. They are:

Methodology

To calculate energy revenues, we estimate a system-wide battery price and multiply this by the aggregated net output of battery resources.

System battery price

The system-wide battery price is calculated using the average price exposed to all battery resource nodes in ERCOT.

A system-wide battery price is used, as the input data into the ERCOT Battery Benchmark is aggregated net output of battery resources in ERCOT. This approach is intended to capture the collective operations of all battery resources.

Assumptions

Using Modo's data on how batteries have been physically operated, batteries tend to be importing power when prices are low, and exporting power when prices are high. Using this insight, at each interval period we calculate energy revenues by averaging the top 50% of prices at battery resource nodes by the exported MWs, and the bottom 50% for imports, and then adding these values together.

All energy revenues are associated with real-time energy prices. This assumption is made on the basis that Day-Ahead energy revenues only contributed to 0.62% of total asset revenues in the last three years (as of 30th May 2024).

Ancillary Services Revenues

Input Data

The datasets we use to estimate ancillary services revenue are:

Methodology

To calculate ancillary service revenues, we estimate the participation of batteries in each ancillary service and multiply this by the market clearing prices.

Ancillary Services Procured

The quantity of ancillary services procured by ERCOT is taken from the Ancillary Service Requirements dataset.

Ancillary Services Awarded to Batteries

To estimate battery participation in Ancillary Services, we take the rolling 30-day average of Ancillary Service capacity awarded to batteries in each delivery hour using our proprietary battery operational data calculated from disclosure reports. Using this battery participation rate, we multiply it by the quantity of Ancillary Services procured.

Assumptions

With ERCOT's 2-day delay in publishing ancillary services volumes, we use the service requirements dataset to estimate total procurement. We assume full capacity is achieved in day-ahead auctions, given that there were only 6 days in 2023 in which >200 MW were procured outside of the Day-Ahead market.

Using a rolling 30-day average of battery participation in Ancillary Services enables us to reduce the noise from small variances in daily participation rates. While these variations currently introduce a minor error in our daily revenue estimates for Ancillary Services, our analysis shows a correlation of 99.7% of ancillary services revenues between the ERCOT Battery Benchmark and the ERCOT Battery Index (looking at values between 6th December 2023 and when the ERCOT Battery Benchmark was released, 30th May 2024).

Accuracy

Using values from the ERCOT Battery Benchmark "nowcast" from December 6, 2023 - we found a 99.8% correlation with the ERCOT Battery Index and a median absolute daily error of $19/MW.