## 3 Results and Discussion
### Propagation of Uncertain Input Variables to Estimate the Electric Generation  
As described in Section 2.1, based on the data described in the previous section, random sampling of the resources has been carried out, so that the generation is determined based on the characteristics of the solar panels and wind turbines, described in Section 2.2. A unitary power of 1 MW has been considered for both solar and wind installations. As summarized in Figure 6, there is a baseline behavior around which sampling variationsoccur; for instance, wind power generation is about 240 MWh during the month of March, with most of the 93 random sampling scenarios in the range of 210 to 270 MWh. Focusing the analysis on the generations, as summarized in Figures 7 and 8, the 93 samples of the monthly average values for both resources and for all locations are shown. Remember that although the monthly values are presented, the calculations have been made on an hourly basis. Figure 6: Random sampling behavior for monthly wind generation in the Mediterranean Region. Figure 7: Average monthly wind generation for the nine terrestrial locations considered: (**a–c**) solar irradiance: high, moderate, and low; (**1–3**) wind speed: high, moderate, and low. As can be seen in Figure 7, wind generation, if averaged values are analyzed, may seem to have a fairly constant generation throughout the year. With monthly values around 100 MWh for low wind locations (Figure 7-3), around 150-250 for moderate wind locations (Figure 7-2), and between 200 and 350 for high wind locations (Figure 7-1), although even reaching values of almost 500 MWh in the case of the Sahara and North Sea coast. Although, as detailed later, when analyzing hourly values, even more significant differences can be appreciated. On the other hand, the graph clearly shows the differences in generation levels between the high, moderate, and low wind zones, with average capacity factors of around 40%, 25%, and around 15%, respectively (Table 4). Despite this relative stability of the monthly average values for all the simulations, depending on the location, it can be seen that there are differences in generation between different periods of the year. For example, in the coastal Sahara area, there are very high generation values throughout the year (Figure 7(a1)), but the winter months, from November to February, show clearly lower values, while in late spring and early summer there are the highest productions, in May, June, and July. In other sites the differences are not so great, but even so there are usually at least two levels of generation, a lower one around the winter months and a higher one around the summer months. Figure 8: Average monthly solar generation for the nine terrestrial locations considered: (**a**–**c**) solar irradiance: high, moderate, and low; (**1**–**3**) wind speed: high, moderate, and low. Regarding solar generation, there are also clear differences between the capacity factors of the three solar PV generation levels, with values around 20, 15, and 10% for high, moderate, and low irradiation zones (Table 5). Additionally, there is usually the previously cited clear difference between summer and winter months (Figure 8), except for those locations with low latitudes, where this generation is more homogeneous. In this line, there are the coastal Sahara and south of Africa areas (Figure 8(a1,a2)) where the radiation remains fairly constant for much of the year (also penalizing the production during the summer months due to the negative effect of high temperatures on the performance of solar panels). The location of the Andean zone of northern Chile (Figure 8(a3)), where irradiation is very high in the summer months (October to March, situation in the southern hemisphere) and quite low in the central winter months, with a high average. As mentioned above, for solar generation, it is important how much is generated and when since there are different periods when generation can be extremely low.