Fraunhofer ISE Energy-Charts Battery Price Simulator (2026)

Fraunhofer ISE’s press release (no. 28, 1 Oct 2026) launching a free price simulator on the Energy-Charts platform, plus the 17-page method description (v1.0, 24 Sep 2026, Leonhard Gandhi). The tool reruns each German-Luxembourg (DE-LU) day-ahead auction from the published bid curves with an added, selectable battery fleet. It is German data, not Swedish; the wiki uses it as an external benchmark for how a large battery fleet compresses day-ahead price spreads. The interactive tool itself was not opened.

Reading scope: the press release was read in full. Of the method document, the abstract, the introduction (sections 1.1-1.4), the input-data table, the day-ahead share section (4.4), the parameter table, the limitations section’s summary box and the comparison with fundamental models (section 11) were read; the detailed model equations, block-order and market-coupling sections and validation were not.

What the simulator does

• Setup. It recalculates the auction using the real buy and sell curves from EPEX SPOT and adds a battery fleet that buys cheap and sells dear to maximise profit over a calendar week. Every added trade shifts the curves and the price all other participants get. Block orders and cross-border exchange are allowed to react, because simply shifting the published curves would overstate the price effect.
• Settings. Fleet power 0-20 GW, storage duration 2-6 hours, and a market scenario (published curves only; with block orders re-cleared; with market coupling to neighbours; or both). Per week, 2,000 combinations are calculated (100 effective power levels, five durations, four scenarios). Results are quarter-hourly, downloadable and updated daily; data is available weekly from 1 Jan 2025.
• Fixed parameters. Round-trip efficiency 86 % and degradation cost 10 EUR/MWh discharged; neither can be changed by the user. A constant day-ahead share (default 20 %) turns fleet power into “effective” day-ahead power, a stand-in for the fleet also trading intraday and in balancing markets. The method derives the default from the RWTH Aachen Battery Revenue Index (monthly values 14-20 % for September 2025 to August 2026, mean 16.5 %).
• Inputs. All public: EPEX SPOT curves and block-order files, JAO Core maximum bilateral exchanges, and ENTSO-E transparency data (prices, load forecasts, schedules and capacities).

Headline result (2025, scenario with block bids and no cross-border trade)

• With 20 GW and 2 hours (40 GWh) of batteries: the average daily spread between the dearest and cheapest quarter-hour falls from 130 to 53 EUR/MWh (-60 %).
• Hours above 200 EUR/MWh fall from 169 to 20, and hours with negative prices from 575 to 271.
• The market value of solar rises 35 %, from 45.08 to 61.02 EUR/MWh.
• On 20 Jan 2025, the year’s dearest day, the evening peak would have fallen from 583 to 221 EUR/MWh; on 11 May, the cheapest day, midday prices would have risen from -250 to -20 EUR/MWh.
• The press release does not say how the “20 GW” relates to the day-ahead share. The method defines effective power as fleet power times day-ahead share, with 20 GW as the top level; read side by side with other fleets, check which one is meant.

Limitations (the authors’)

• Day-ahead only. Intraday, balancing, redispatch and grid relief are not modelled; the press release says revenues and benefits from those are “additional factors”.
• A what-if, not a forecast. All other bids stay fixed, so it is a short-term sensitivity, not a new equilibrium. The constant day-ahead share is called “not realistic”, and perfect one-week foresight, 86 % efficiency and 10 EUR/MWh degradation cost are idealised inputs with a large influence on results. It is not a statement about total storage project revenue, and the physical system (curtailment, emissions, system costs) is not modelled.
• Funding. Development was financially supported by ECO STOR, the German Association for New Energy Economy (bne), Harmony Energy, Return J&P, BELECTRIC, MaxSolar, FENECON, Kyon Energy Solutions and Remmers Solar; all are storage, solar or industry-association backers.

Relevance to existing wiki topics

• Energy Storage — a bid-curve-based benchmark for spread compression by large battery fleets, next to the Clean Horizon revenue index (Source - Clean Horizon Storage Index (2026))
• Merit-Order Price Suppression from Weather-Dependent Generation — the solar market-value effect is the same cannibalisation mechanism, here in reverse