MOTIVATIONS

Solar renewable energy is increasing its presence in the large scale electric power supply. However, nowadays its weighted importance within the energy mix is still far from its theoretical potential. Notwithstanding, as mentioned before, its expectations of growth for the next decades are the highest of all the renewable energy sources. This prospective growth will be driven by technological and economic dynamics, which are unfailingly interconnected. The rate of penetration will be associated with the capability of providing solutions that can align the technical knowledge advances with the economic benefits, beyond the initiatives of the different governments and public institutions. In this way, today many of the efforts in the field of solar energy are focused on reducing costs while protecting the security of the electricity supply. The present research work focuses on those concerning the solar resource.

Within the topic of solar energy, in addition to the technology of exploitation itself, there is an eminently essential aspect, namely the solar resource. This primary source of energy -the solar irradiance reaching the earth surface- and the meteorological factors that affect it, naturally determine in a direct way the most important aspects associated with solar energy, which are the development and integration of this renewable source in the power supply structures, both at generation and distribution levels. In addition, the solar resource also conditions the technology of exploitation, being determinant for all of them. Over the last recent years there has been an increase in the interest and, in parallel, an increase in the research associated with this matter in its two main dimensions: the assessment and the forecast of solar resource. Most of this research follows a distinctly practical pathway, providing solutions and answers to each particular problem posed by the solar industry. However, there are many questions that are far from being solved, despite the fact that several alternatives have been proposed. At the same time, there are solutions that need to be developed in greater depth so that they can reach the potential that is expected from them. In both circumstances, the elaboration of rigorous

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works that are scientifically validated is of great importance, since they contribute to the development and integration of the solar renewable energy in a real way -in a practical sense– when assimilated and applied by the solar industry. In this respect, it is the industry itself which demands this type of high valuable works that help the growth of the sector. The elaboration of the research study presented in this thesis decidedly follows this orientation, contributing with new solutions and deepening in others, both in the scopes of solar resource assessment and solar resource forecast.

Regarding solar irradiance assessment, one of the major current issues for the industry concerns the need to have the most reliable information possible about the solar resource, in order to carry out the decision making in solar projects. In particular, promoters are required by financial institutions to conduct objective feasibility analysis of their projects, with high dependability of the expected performance of the solar energy based facilities during their life-time. These performance analyses are carried out based fundamentally upon time series of solar irradiance data. These time series should be able to objectively characterize the long term performance of the solar plants. These performance studies are made in terms of the estimated production capability of the facility, according to its expected behavior under certain stress scenarios that usually consider annual periods of low solar energy availability. The definition of such scenarios, together with the uncertainty parameter derived from the solar energy assessment, are of key importance, because they determines essential aspects of the projects feasibility, such as the return of investment and financial costs. Therefore the quality of the information contained in the datasets used and its later processing to obtain such valuable information are decisive. It is precisely the definition of such scenarios that represents one of the current difficulties in the field of solar resource assessment. As explained in the previous section (vide supra Section 1.2 State-of-

the-art), these scenarios are established based on historical long-term

time series of surface solar irradiance –and other meteorological variables of interest- and described in terms of the so-called typical meteorological year (TMY) –or the most recent concept of typical solar

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year (TSY)-. The problem is founded on the fact that there is not a common unified method for generating TMYs that is widely accepted by the scientific community. Further more, the existence of different methodologies for TMY generation evidences the lack of scientific consensus about this question. Moreover, the current methods are scarce. From them not all allow for generating TMY for any probability scenario of solar resource availability (Cebecauer and Suri, 2015). In addition some of them are under discussion and some problems have been detected (Blanc, 2015). Finally not all of them are public, but they are part of the private knowledge of certain companies that provide this kind of consulting services. Nevertheless, from the standpoint of the final users of the solar industry the possibility of obtaining two different results for the same data source introduces an extra factor of uncertainty, which remains uncontrolled. Althougt TMY is a tool that does not account with the favor of the scientific experts, it is so used in the solar industry that it remains to be a key tool for solar projects. Hence, due to its practical and extensive use, an endeavor for a unified scientific answer is therefore ineluctable. The aim is to develop a standard method for TMY generation that can generate confidence by having a broad scientific consensus and contributes to enhance the bankability of the projects.

On the other hand, to integrate a variable source like solar energy into the energy supply structure on a large scale compromises the operability of the system, which must work under the principle of security and stability, while the production should be balanced with the expected demand. In addition, producers need to know the expected resource that will be available in order to program the plant operation and management, as well as to plan the better strategy for participating in the electricity market. In this sense, it is usual to apply a policy of penalties against the deviations announced in advance by the producers to the TSOs. These penalties reduce the potential revenues of the plant respect to the case of 100% of forecast reliability, that is, without any deviation. Furthermore, to know the solar irradiance with certain foresight would expand the possibilities for improving the profitability of the plant, for instance by means of its participation in special

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markets that are more rewarded, like the so-called adjustment markets. Hence, solar radiation forecasting will be a key tool for effective scheduling, improving decisively the competitiveness of solar energy. Thus, it can be concluded that the final problem is not so much the variability of the solar radiation, but its predictability (IEA, 2008). Therefore, solar industry demands a specialized reliable forecast of solar resource for all useful periods in plant operational phase. Among the methodologies for solar radiation forecasting, NWP models stand out as the most powerful tool. They provide comprehensive forecasts on a physical base for short and medium ranges –for minutes up to days ahead- for both single locations and extended regions, with high resolution in space and time. In particular, the WRF regional model is one of the most advanced NWP currently in the world. It is widely supported and developed by the scientific community, being in the state-of-the-art of numerical weather modeling. Nevertheless, NWP models have not been specially designed for the application of solar irradiance forecasting to the solar energy sector. Even more, the knowledge about the skillfulness of the model to predict solar irradiance is far from being widely studied. Main issues remain unknown. It is necessary to understand the specific behavior of the model when forecasting solar irradiance. In particular, the forecast of DNI component remains little investigated. Thus, it is basic to know the model performance under different cloudiness situations, the stability of the predictions respect to the forecast horizon and how is the skill of the model predicting GHI and DNI. In addition, it is very important to benchmark the forecasts against other models, so as to establish a reference framework that allows understanding not only the performance of the model in absolute terms, but also in relative ones. Finally, it is essential to know if higher resolutions, which a priori mean a better representation of the physical phenomena, provide better results when evaluating solar radiation forecasts (Stensrud, 2007). This provides a better insight about the model performance to forecast solar irradiance. All in all, this research provides a better understanding of the capabilities of WRF model providing solar irradiance forecasts and its applicability to the solar industry regarding the integration of this source of energy into the power supply structures.

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To summarize in a general way, the research work of this thesis is motivated for the need of answering several relevant questions that remain unknown or incomplete, but that are of key importance for the application of the state-of-the-art knowledge to the solar energy sector. In particular, the interest lies on enhancing the competitiveness of the solar energy through the improvement of the solar resource assessment and forecast in the specific aspects described above.