Serbia’s day-ahead market recorded an almost EUR 179/MWh gap between its daily low and the hour-20 peak on 15 October, illustrating the potential value of battery flexibility. The spread alone is not a bankable measure of revenue because it does not establish whether a battery can capture those prices. Its earnings depend on the hourly market and the asset’s operating constraints.
The price was near EUR 189.9/MWh at the daily low and reached EUR 368.6/MWh at hour 20. In an illustrative calculation using 90% round-trip efficiency, a battery buying 1 MWh at the low would return 0.9 MWh after efficiency losses. Selling that energy at the peak would produce about EUR 332 against roughly EUR 190 in charging costs, leaving around EUR 142/MWh in gross capture.
That estimate excludes degradation, fees, imbalance costs, the optimiser’s share and financing costs. It also assumes the battery can charge at the low and discharge into the expensive hour. The order of hourly prices, battery duration, efficiency, state of charge, market access and degradation all affect the amount it can capture. A daily high-low comparison therefore does not establish achievable earnings.
Price patterns can change the outcome even when the daily extremes are the same. Several low-price hours followed by several expensive hours can give a two-hour battery and a four-hour battery different revenue profiles. A battery that begins the day partially discharged may miss the best charging window, while one reserved for balancing services may deliberately keep capacity unavailable for arbitrage.
Regional prices and asset-level capture
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 gap between the highest and lowest Southeast European markets was EUR 60.30/MWh, although the listed Serbia and Greece averages differ by EUR 61.32/MWh.
A battery cannot directly monetise a geographic price spread without transmission capacity and trading positions. It captures price differences over time at its own node or bidding zone, so regional baseload comparisons do not by themselves show what a specific asset can earn. Its market access and operating limits determine whether it can act on price changes.
A bankable model should simulate the asset 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 because storage itself changes the hourly price curve. Lenders should value dispatchable hourly capture, rather than the difference between the single cheapest and most expensive hour.