Battery lenders in Southeast Europe should use probability ranges, rather than a single P50 revenue forecast, to size debt as electricity-market volatility and new storage capacity increase uncertainty, a battery-financing analysis says. The approach matters because competing batteries can reshape prices and reduce project revenues over time.
The analysis recommends modelling multiple hourly price paths and operating conditions, then translating P10, P50 and P90-type outcomes into cash flow, debt-service coverage and covenant headroom. A simulation based on the battery fleet at financial close can be materially wrong by a project’s third or fourth operating year as new capacity enters service.
Storage growth is already visible in Romania, where installed power increased from 494 MW on 1 January 2026 to 1,162 MW by 1 October 2026. Bulgaria’s fleet exceeds 6.2 GW and 19 GWh, adding to the capacity lenders need to consider when forecasting revenue.
Price shape and revenue concentration
During Week 42, regional baseload averages across major Southeast European markets ranged from EUR 186.57/MWh in Greece to EUR 247.89/MWh in Serbia. Those averages do not show the intraday price shape that determines a battery’s actual revenue, the analysis says.
A relatively small change in the evening price premium can remove a large share of gross margin. The analysis identifies a key stress scenario as a modest but persistent narrowing of daily spreads combined with lower ancillary-service prices. Lenders should test this against project cash flow instead of assuming the battery fleet remains unchanged.
Banks should assess how many hours drive annual EBITDA, how much revenue comes from the top price events and how returns change if those events become less extreme. A battery reliant on a small number of scarcity hours carries a different credit risk from one whose revenue is diversified across several markets and services.
Probability ranges should drive debt sizing, with the resulting cash-flow, debt-service coverage and covenant-headroom outcomes showing how much debt a project can support under different conditions. The analysis argues against basing lending decisions on one expected-price forecast.
