Croatia’s wind fleet shows how annual capacity factors can obscure the operational and commercial behaviour of a large wind generation fleet. Hourly output varies sharply, creating a balancing challenge for the electricity system and potential costs for market participants. The January and February figures also illustrate why correlation between projects matters when assessing a portfolio.
In January 2026, Croatia had 30 wind farms in regular operation, with total installed capacity of 1,237.15 MW. Two more projects, totalling 77 MW, were under construction or trial operation. The operating fleet generated 250,003 MWh during the month, giving it a capacity factor of 25.57%.
Hourly production ranged from 958.83 MWh in January’s strongest hour to just 3.79 MWh in its weakest. Daily output varied between 1.79 GWh and 19.12 GWh. In February, the strongest hour reached 1,016.42 MWh, while output fell to zero in the weakest hour; the month’s capacity factor was 26.2%.
Output swings and imbalance exposure
For investors, the figures show that a portfolio capable of producing around 1 GW in one hour can behave almost like a different asset several hours later. The financial implications start with forecasting: wind farms nominate expected production before delivery. As forecasts improve closer to real time, traders can adjust their positions through the intraday market. Some deviation nevertheless remains when actual output is measured, and the balancing system must absorb the difference.
Who ultimately pays for that difference depends on the market and contractual structure. A wind farm may carry imbalance exposure directly, while a trader may absorb it in return for a fee or a less attractive PPA price. An aggregator may manage several assets together. In each case, variability carries a cost even when the wind resource itself is free.
Aggregation does not automatically remove that cost. If projects are exposed to the same regional wind pattern, their output can rise and fall at the same time, making the diversification benefit smaller than the number of assets might suggest. The relevant measure is correlation: wind farms hundreds of kilometres apart can still have strongly correlated output if they experience the same large-scale weather system. By contrast, assets in different wind regimes may offset one another even within a smaller geographic area.
Portfolio correlation and regional concentration
This distinction is likely to matter increasingly for wind portfolios across Southeast Europe. Developers assembling several assets should assess not only each project’s P50 production but also the covariance between hourly production profiles. Lenders financing a portfolio should establish whether the projects genuinely reduce volatility or simply combine correlated generation.
The same issue applies to PPAs. A corporate buyer purchasing output from several wind farms may expect diversification to produce a relatively smooth delivery profile, but that assumption can fail if the plants respond similarly to regional weather. The portfolio may then overproduce collectively during strong-wind periods and underproduce during weak ones. Exposure to replacement power can increase precisely when market prices are high.
Transmission geography adds another source of correlation. Many Croatian wind farms are concentrated in coastal and southern regions with attractive wind resources. The Croatian Transmission System Operator (HOPS) reported that the operating fleet in early 2026 was concentrated particularly in Zadar, Šibenik-Knin, Split-Dalmatia, Dubrovnik-Neretva and Lika-Senj counties. Clustering can create project-development economies of scale, but it can also concentrate injections into shared parts of the network, making the combination of correlated weather and common grid infrastructure relevant to asset valuation.
Storage and balancing services
Storage may eventually mitigate some variability, but it is not a generic solution. A battery intended to absorb brief forecast errors requires a different operating strategy from one designed for two-hour wholesale arbitrage. A battery used to firm a PPA may also need different power and energy characteristics from one primarily used for balancing services.
Croatia’s balancing framework is becoming more open. HOPS allows technically prequalified individual network users, aggregators, independent aggregators and renewable-energy communities to provide balancing services, subject to qualification and contractual requirements. This creates an opportunity to turn variability into flexibility, but it first requires recognising the asset’s physical behaviour.
Annual production smooths out extremes, while debt, PPAs and electricity systems experience them hour by hour. Croatia’s wind fleet therefore provides a warning for investors across Southeast Europe: portfolio output depends not only on how much energy it produces over a year, but also on how often its wind farms rise and fall together and what that correlation costs when the system responds.