Croatia’s wind fleet shows how annual capacity factors can mask the operational and commercial behaviour of a large wind-generating portfolio. January and February output data reveal wide swings in hourly production. Those changes matter for balancing, asset valuation and contractual exposure.
Wind output varied sharply by hour
In January 2026, Croatia had 30 wind farms in regular operation, with a combined installed capacity of 1,237.15 MW. Two additional projects, totalling 77 MW, were under construction or in trial operation. The operating fleet generated 250,003 MWh during the month, giving it a capacity factor of 25.57%.
Hourly and daily output varied substantially. The fleet’s strongest hour in January reached 958.83 MWh, while production in its weakest hour was just 3.79 MWh. Daily generation ranged from 1.79 GWh to 19.12 GWh.
February showed a similar pattern, with the strongest hour reaching 1,016.42 MWh and the weakest recording zero output. The month’s capacity factor was 26.2%. For the electricity system, these swings create a balancing challenge; for investors, they show how a portfolio producing around 1 GW in one hour can behave almost like a different asset several hours later.
Forecasting and portfolio correlation shape exposure
Financial exposure begins with forecasting: wind farms nominate expected production before delivery, and traders can adjust their positions through the intraday market as forecasts improve closer to real time. Some deviation remains when actual output is measured, and the balancing system must absorb the difference. Who ultimately pays depends on the market and contractual structure.
A wind farm may carry imbalance exposure directly, while a trader may take it on in exchange for a fee or a less attractive power purchase agreement (PPA) price. An aggregator may manage several assets together. Whatever the arrangement, variability has a cost even when the wind resource itself is free.
Aggregation does not automatically remove that cost. Projects exposed to the same regional wind pattern may see production rise and fall together, making the diversification benefit smaller than the asset count suggests. Correlation is therefore a relevant metric: wind farms hundreds of kilometres apart can still have strongly correlated output if they face the same large-scale weather system, while assets in different wind regimes may offset one another over a smaller geographic area.
This distinction is likely to matter increasingly for wind portfolios across Southeast Europe. Developers assembling several assets should assess both each project’s P50 production and the covariance between hourly production profiles. Lenders financing portfolios should determine whether the projects genuinely reduce volatility or simply aggregate correlated generation.
The same issue applies to PPAs. A corporate buyer sourcing output from several wind farms may expect diversification to create a relatively smooth delivery profile, but that assumption can fail if the plants respond similarly to regional weather. The portfolio may then overproduce collectively in strong-wind periods and underproduce in weak ones, increasing replacement-power exposure precisely when market prices are high.
Grid concentration and flexibility options
Transmission geography adds another dimension to correlation. Many Croatian wind farms are concentrated in coastal and southern areas with attractive wind resources. HOPS reported that the operating fleet in early 2026 was particularly concentrated in Zadar, Šibenik-Knin, Split-Dalmatia, Dubrovnik-Neretva and Lika-Senj counties.
Clustering can create economies of scale in project development, but it can also concentrate injections into shared parts of the network. The combination of correlated weather and common grid infrastructure therefore warrants attention in asset valuation.
Storage could eventually mitigate some variability, but it is not a generic solution. A battery designed to absorb brief forecast errors requires a different operating strategy from one intended 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 first requires recognising the asset’s physical behaviour.
Annual production smooths out extremes, while debt, PPAs and electricity systems face them hour by hour. For investors across Southeast Europe, the relevant question is not only how much energy a portfolio generates over a year, but how often its wind farms rise and fall together—and what that correlation costs when the system has to respond.