Serbia’s day-ahead market recorded an almost EUR 179/MWh difference between the daily low and the peak in hour 20 on 15 October, highlighting the potential value of battery flexibility. However, this spread is not a bankable revenue measure, because earnings depend on the hourly prices and operating constraints an asset can actually capture.
The day-ahead price stood near EUR 189.9/MWh at its daily low and rose to EUR 368.6/MWh in hour 20. In an illustrative calculation using 90% round-trip efficiency, a battery buying 1 MWh at the low and selling 0.9 MWh after efficiency losses would earn about EUR 332 in sales against roughly EUR 190 in charging costs, leaving around EUR 142/MWh in gross capture.
This illustrative figure excludes degradation, fees, imbalance costs, the optimiser’s share and financing costs. It also assumes the battery can charge at the low and discharge during the high-price hour. The outcome depends on the sequence of hourly prices, battery duration, round-trip efficiency, state of charge, market access and degradation.
Operating constraints and regional price differences
Price patterns can matter as much as daily extremes. Several low-price hours followed by several expensive hours can yield different revenue profiles for a two-hour battery and a four-hour battery, even if both face the same maximum and minimum prices. A battery that begins the day partly discharged may miss the best charging window, while one reserved for balancing services may intentionally keep capacity unavailable for arbitrage.
In Week 42, average baseload prices were EUR 247.89/MWh in Serbia, EUR 246.87/MWh in Hungary, EUR 240.51/MWh in Romania, EUR 235.89/MWh in Bulgaria, EUR 230.49/MWh in Croatia and EUR 186.57/MWh in Greece. The reported difference between the highest and lowest Southeast European markets was EUR 60.30/MWh, although the listed Serbian and Greek averages differ by EUR 61.32/MWh.
A battery cannot directly monetise a geographic price difference without transmission capacity and trading positions. Storage instead captures price differences over time at its own node or bidding zone, so regional baseload comparisons are distinct from revenue an asset can achieve.
A bankable model should simulate the battery hour by hour across many price paths, enforce charging and discharge constraints, include auxiliary load and degradation, and calculate debt-service metrics. Multiplying a fixed number of cycles by an average spread is too crude, as storage itself changes the hourly price curve. Lenders should value dispatchable hourly capture, rather than the gap between the single cheapest and most expensive hour.