## 3 Techno-Economic Analysis at 2060  
### Materials and Methods  
In this section, the authors present a long-term approach that aims to evaluate the electricity costs produced by floating offshore wind farms in Italy, considering effects of climate change on wind energy production and further costs optimization due to development and large diffusion of this technology. The difficulty in conducting studies of this type arises from the multidisciplinary approach that must be applied. In order to set up a comprehensive long-term predictive methodology, it is necessary to consider the interactions between the development of the technology, the costs and the market, the climate, and sociopolitical dynamics (the latter is out of the scope of this study) of the next decades. Forecasting the evolution of all these issues is not simple, given their complexity [25]. Concerning the costs, in Section 2 an extensive assessment at 2030 was reported. In this section, the economic benefits beyond 2060, such as long-term progressive decrease of costs and weighted average cost of capital (WACC) due to the learning curve, and reaching large diffusion of floating wind technology, are considered [26]. Climate change has potential impacts on the whole energy sector, but especially on renewables. Several studies provide risks analyses and predictions of future resource availability [27]. The focus of the present study is on the change in spatial distribution of wind resources, and possible effects on wind energy productivity and, consequently, on economic sustainability of wind farms in Italian seas. Obviously, a reduction in mean wind speed generally leads to a drop in power production and, accordingly, to an increase in LCoE. Otherwise, a higher resource is favored in terms of economic sustainability. Current resource distribution reproduced in wind charts and atlases is based on historical data recordings and on climatic models fitting those data. Uncertainties arise because of an incomplete knowledge of atmospheric processes and because of lack of data, especially offshore, where there are very few measurement stations. Future spatial and temporal variations of meteorological parameters, such as temperature, precipitation, and mean wind speed, are estimated by simulations carried out with regional climate models (RCMs), whose boundary conditions (which include CO\({}_{2}\) emission pathways, as provided by Intergovernmental Panel on Climate Change, IPCC) are derived from global climate models (GCMs). Uncertainties related to these models are often softened by running different simulations constituting an \"ensemble\" or by validation through comparison with empirical data sets [25; 28]. Concerning the possible impact of climate change on the production expected from wind power plants in the future, the studies are focused on mapping the wind speed and identifying the areas that, in long-term scenarios, will benefit from an increased wind potential, and areas that will be negatively impacted [28]. Since wind energy density increases as the cube of the speed, even small variations in wind speed are amplified in the production calculation [25]. Moreover, to depict a complete frame about economics, the trend of other LCoE drivers, such as CAPEX, OPEX, and WACC were investigated. In order to carry out this analysis, a parametric tool similar to the one presented in Section 2 has been developed. For the second generation of floating wind parks to be installed in 2060, the starting base case was the 30-year life cycle--1000 MW reference wind power plant already used in the 2030 analysis, and the central values of the previous cost analysis were applied. Moreover, for the baseline,no wind resource variation was supposed, since reference literature examined in this study do not show significant modifications of wind speed patterns over the area of interest in the next decade.