## 3 Techno-Economic Analysis at 2060
### Materials and Methods
According to ATLAEOLICO [21], Italy's wind power productivity maps, shown in Figure 2, indicate Apulia, Sardinia, and south Sicily's coasts as the more attractive regions for installation of new offshore wind plants. In fact, in these areas, the average wind speed is closer to the North Sea or Atlantic one, where higher mean wind speeds occasionally exceed 12 m/s. Firstly, as an exemplary demonstration, three hypothetical case studies were arranged in these three marine areas, about 40 km from the coastlines, at less than 500 m water-depth. The ATLAEOLICO performance calculator tool was employed to find out the power productivity of a theoretical parametric floating wind farm, given the geographic coordinates of the site and the hub height of the selected wind turbine. This tool is applied in the reference case and for all of the other production evaluations. Wind speed at hub height is automatically extrapolated by the software through vertical gradient wind intensity equation. Secondly, we introduced parameters to represent long-term scenarios at 2060. To evaluate possible variations in wind resources due to climate change, the authors mainly refer to the above mentioned study [28] that analyzes the results, and the level of accord of six different simulations performed with three RCM (KNMI-RACMO2, HIRHAM5, RCA3) and four GCM (BCM, ECHAM5, ECHAM5-r3, HadCM3Q16). General conclusions of the paper are that, although some delimited regions could experience an increase in mean wind speed, the wind resource in the Mediterranean area will generally undergo a modest decrease (especially in the Central Mediterranean) or remain constant. A comparable tendency is extrapolated for Italy: models agree on a slight reduction (up to \(-\) 0.5m/s) over Sicily and Calabria's coasts, while there is not an obvious trend for the rest of the Italian seas. This picture is also confirmed by the simulations conducted with a RSE tool, called CLIMED [29], aimed to assess the impacts of climate change on the electricity system. Even in a scenario with high  
Figure 2: A view of ATLAEOLICO mean wind speed map at 100 m a.g.l/a.s.l. The three case study sites are shown: (**1**) Apulia, (**2**) Sicily, (**3**) Sardinia. emissions, the decrease in wind speed on Italian seas is limited to \(-0.4\) m/s and seems concentrated around Sicily. Nevertheless, even though some general patterns may be distinguished, it must be accounted that perceptible discrepancy still exists between long-term projections provided by different sources. Accordingly, a conservative approach was applied in determining long-term resource decrease estimates. Chosen values should be intended as the worst scenario that could incur based on the sources analyzed in this section. We set for case study \(1\) (Apulia) a null variation of wind speed, for case study \(2\) (Sicily), due to the scarce level of agreement of predictive models, two \(-0.25\) m/s (less pessimistic) and \(-0.5\) m/s (pessimistic) hypothesis and, finally, for case study \(3\) (Sardinia), a decrease of \(-0.25\) m/s. The new values of wind speed were re-implemented in ATLAEOLICO and, for each case study, future estimates of wind power productivity were obtained as reported in the following Tables 5-8. Regarding economic inputs, projections of the main parameters, CAPEX and OPEX, at 2060 were extracted from NREL reports [30; 31], which contain mid and low cost trends, and allowed to develop more or less optimistic scenarios. Distance-from-shore-dependent costs, such as grid connection expenses, were considered in the 2030 scenario. In order to represent more fortunate evolutions to 2060 of the floating wind sector, the WACC was gradually lowered to 2.5% [24]. Wind farms and turbine sizes are expected to change as well. To describe this increasing trend, we introduced a second reference 2000 MW wind power plant, composed by 100 20-MW turbines.