​German battery storage is growing fast. To scale beyond the 3 GW online today, asset-level revenue data is more important than ever. Public asset-level operational data, which underpins Modo's GB index, doesn't exist in Germany. The alternative is a virtual benchmark: a simulated asset, cross-optimised across real market data. A transparent methodology gives all parties confidence in the value of this benchmark.

Modo Energy's German BESS revenue benchmark is now live on the terminal, with neutral 1h, 2h, and 4h benchmarks as well as the option to customise your benchmark. The benchmark tracks what a battery could have earned each day across day-ahead, intraday, FCR, and aFRR, using actual market prices that update every day.

• The German benchmark simulates a virtual battery cross-optimised in day-ahead, intraday, FCR, and aFRR, refreshed with live market prices.
• Imperfect foresight recreates real market conditions. A 2h rolling perfect-foresight window simulates intraday re-optimisation. aFRR capacity bids are capped to account for real optimiser behaviour in a pay-as-bid market without giving the model unrealistic access to information.
• An 80% calibration factor brings simulated revenues into line with realised performance, as validated against GB, where both virtual and real-asset data are available.
• The benchmark is fully customisable. Users can change duration, round-trip efficiency, daily cycle limits, day-start state of charge, and exclude ancillaries for a baseline day-ahead and intraday view. FCA terms such as ramp rates, ancillary limits, and other market-specific constraints will be added to the customisable benchmark in the coming weeks.

To learn more about the German benchmark, reach out to the team - till@modoenergy.com and amit@modoenergy.com

Why a benchmark matters for the German market

Every liquid commodity market has a working benchmark. Battery energy storage in Germany has not had a single, reliable, transparent source of truth until now. A neutral, market-wide reference enables participants to do four things:

1. Track where revenues are going. Owners, investors, and offtakers can see whether the market is expanding or contracting, independently of any individual asset's performance.
2. Benchmark optimiser performance. A transparent potential number lets owners hold optimisers to account against an independent reference, instead of each provider's own framework.
3. Settle liquidated damages. Some unavailability contracts reference a market rate; without one, disputes drift to court.
4. Settle route-to-market and virtual contracts. Index-linked PPAs, floors, and swap structures need a transparent settlement reference.

Modo Energy’s benchmark closes this gap with a neutral number, with an open and transparent methodology to make all market parties comfortable with the values used in these contracts.

How the methodology works

The ME BESS DE uses Modo Energy’s battery dispatch model to indicate how a representative battery would have operated in the German market using real prices.

The first layer of this is the battery dispatch across markets. The model bids a representative asset into the day-ahead auction, intraday auction and continuous market, as well as FCR and aFRR. Prequalification rules for ancillary services are encoded: minimum and maximum bid sizes, aFRR energy activation prices, and energy reservation requirements all bind the schedule the same way they would in real prequalified operations.

Real-life ancillary activations affect the state of charge of the battery, making post-activation management part of the model. This also explains negative intraday revenues in some months, where the battery has to recharge in the intraday continuous market after ancillary activation to hit state-of-charge requirements for the next ancillary block.

The chart above shows one example day, 22 March 2026. FCR is booked across the whole day in 4 h blocks at 25–35 MW. aFRR Capacity stacks above and below the FCR block, varying in 4 h windows. This is cross-optimised with day-ahead spread optimisation, wherever the battery can generate the most value. The morning peak pulls the asset into day-ahead discharge, the early-afternoon solar wave pushes it back into charging at negative prices.

The second layer is imperfect foresight. Real operators do not know intraday prices when they bid into the day-ahead auction. The German benchmark model is solved in three steps: day-ahead auction (including ancillary capacity auctions), intraday auction, and intraday continuous (including cross-optimisation with aFRR Energy activations).

Imperfect foresight is further applied in aFRR capacity prices, which are paid in a pay-as-bid auction. The benchmark caps prices at €50/MW/h (the historical P95 value), cutting off extreme price spikes which real optimisers are unlikely to capture consistently.