Back in 2019, we started with a simple question:
How much money do batteries in GB actually make?
While the nuances of answering this question can be challenging, at its heart, it's actually pretty simple! The process for figuring it out looks a little like this:
Identifying assets - Finding as much information about as many battery energy storage sites as we can (including which markets they operate in).
Data collection - Sourcing, cleaning and processing data for each of those markets.
Creating asset schedules - Matching each asset to its contracts, trades and positions, to create a schedule of what it's doing at all times.
Calculating asset charges - Calculating charges based on each asset's location and connection type.
Quality assurance - Aggregating the half-hourly schedules and asset charges to produce the Leaderboard, and performing quality assurance tests.
Publishing the Leaderboard - Sharing the finalised version of the Modo Leaderboard.
Each of these steps comes with its own challenges. This article acts as a jumping-off point for learning more each one.
Identifying assets
By using our knowledge of GB battery energy storage systems (BESS), staying on top of press releases, and keeping a close eye on market data, we're able to build a complete picture of market participants. We use all of this to build our internal GB BESS asset database, which informs the Leaderboard.
We keep track of lots of details for each asset. These include the rated power of a given asset, the current optimisation partner, the postcode of the site, and much more. All these details play a vital role when putting together the Leaderboard.
Data collection
We collate and curate data from numerous sources, including National Grid ESO, DNOs (e.g. UK Power Networks), ELEXON (BMRS), EPEX SPOT, and Nordpool. We also use Modo's proprietary data, which includes our battery asset database, market ID maps, and asset performance information from previous Leaderboard months.
We collect data via several methods: using APIs (Application Programming Interfaces), FTPs (File Transfer Protocols), and in some cases scraping algorithms, e.g. determining Distribution Use of System charges (DUoS) by scraping the Schedule of Charges spreadsheets from each DNO.
This data is continually updated on our servers to support the Modo platform.
Creating asset schedules
Next, we build a picture of what each asset is doing across the month, according to their market IDs. So, for each market ID (e.g. FFR_ID, DC_ID, BMU_ID, CMU_ID), we produce a schedule of operation on a settlement period basis throughout the month.
This stage is vital for identifying gaps in operation, or any changes in asset IDs. When creating the market schedule, our algorithms let us know of any new battery asset IDs that have entered the market (which may be unaccounted for - if we haven’t already found them, that is).
Calculate asset charges
We calculate the use-of-system charges payable to/from all assets for each settlement period throughout the month.
Variable DUoS - We calculate the energy-based DNO costs associated with the asset's connection. (To find out more about DUoS works, check out our Energy Academy video here.)
Balancing Services Use of System charge (BSUoS) - We calculate the applicable BSUoS costs (import and export) for each asset. (To find out more about how BSUoS works, check out our Energy Academy video here.)
Transmission Network Use of System (TNUoS) - Asset-specific TNUoS tariffs are calculated for both generation and demand. (To find out more about TNUoS works, check out our Energy Academy video here.)
The final part of this process is matching each of these charges to/from the correct assets, according to the information in our asset database (such as location and grid connection).
Quality assurance
Quality assurance is by far the most critical stage of the Leaderboarding process. The research team reviews each asset individually, creating a view of that asset’s market activity across the month.
Before we publish the Leaderboard, the Modo team gets around the kitchen table and discusses each asset in detail, checking for periods of unavailability or unusual behaviour (e.g. maintenance, testing, market pre-qualification, etc.). It's at this stage that we identify any notable anomalies or discrepancies in asset revenues, and make the necessary fixes or adjustments. When we publish it, we must be confident in the Leaderboard, including any methodology revisions, upgrades, and policy or market changes.
As such, this is a largely manual (and often painstaking) process.
Publishing the Leaderboard
We then normalise each asset’s earnings on a £/MW basis, and rank them in the Leaderboard from highest to lowest (for that month). We also calculate year-to-date earnings and annualised earnings.
Finally, we give the whole thing the once over, and publish the Leaderboard. Voilà!