## 4 Conclusions  
The main aim of this paper was to present a straightforward and comprehensive method to determine the PDF of the solar irradiation, addressed to handle the inherent variability of the solar resource for the techno-economic assessment of the energy assets. The final product of this methodology is a set of PDFs that characterizes the solar irradiation of the desired site and for a selected time resolution, which can be used as a solar irradiation database when assessing CSP and PV projects. In this regard, a second objective of the paper was to illustrate the selection of the best satellite database available for a determined location, which is exemplified on the country of Morocco, applying it to 23 representative cities belonging to the different climatic zones. Morocco being one of the most outstanding countries in the active promotion of solar energies in the MENA region, the presented method can be a useful tool for the accurate assessment of these projects. First, monthly solar irradiation data were retrieved from various satellite databases (PVGIS-SARAH, PVGIS-ERA5 and PVGIS-CMSAF). The DNI and the GHI were the types of solar irradiation data used when applying the method. A quality control was performed on the retrieved data in order to determine which of the considered databases presented the lowest statistical errors. From the quality control results, the databases PVGIS-CMSAF and PVGIS-SARAH were considered the most convenient for characterizing the DNI and the GHI, respectively. Next, a probability distribution fitting test was presented, able to identify bimodal behaviours in the irradiation data. When the bimodality was confirmed, a kernel distribution function was applied. Conversely, the set of data was regarded as unimodal and the PDF that fitted best was chosen. It can be concluded that for both the DNI and the GHI cases, the extreme value, the logarithmic and the normal PDFs are predominant for the extensive set of Moroccan cities examined. On the other hand, other distributions are not that often. Likewise, the bimodal behaviour appears in some instances but does not follow a recognizable pattern. These varied results remark the need for incorporating the characterization of solar irradiation at the different climatic zones when undertaking the economic feasibility analysis of solar energy assets. The main merit of the presented methodology is that it is composed of simple and clear steps making use of widely known statistical tools, and therefore it is an easy application when compared with the use of other state-of-the-art methods, as ANN. When it is simply needed to embed the radiation uncertainty in the analysis, as is the case of the techno-economic valuation of solar energy assets, the presented methodology can reach this objective with much less complexity and less demanding input data. Figure 14: Evolution of the GHI average for October in Rabat according to the number of samples obtained in the Monte Carlo simulation. Source: own elaboration. In order to assess the validity of the proposed methodology, the obtained PDF for the GHI of the month of October in the city of Rabat was employed in a Monte Carlo simulation, resulting in an average monthly GHI of 137.01 kWh/m\({}^{2}\). This value was then confronted to the most recent satellite data corresponding to the same city and month, i.e., the year 2020. A relative difference of 1.5% was obtained, thus evincing the goodness of the method for representing the stochastic pattern of the irradiation. The results obtained in this paper can be used for future solar related projects. A monthly interval set of data can be useful for long-term studies, whereas a smaller interval is favourable when it comes for a more technical point of view. The reliability of the data is also important, as a low trustworthiness can lead to complications in a project assessment.