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The goal of this Master thesis project was to design a methodology that helps to analyze a set of indicators that can support the decision-making process, by identifying energy strategies with a temporal horizon 2030-2050 in Cuba. Several sources of data and methodologies were used to fulfill the objective. The energy planning model created by Madrazo during her Ph.D. thesis was used as the main tool in this project. The hourly demand and the wind and solar capacity factors have been used as input data for this model. A post-processing module was created in R code, with the objective of analyzing the behavior of the six technical indicators that the model offers as output. The Principal Component Analysis (PCA) method was used as an exploratory method to identify cluster that later allowed studying in detail the particular characteristics of these indicators. Different graphics were used to visualize the performance of the technical indicators under different conditions, which allows us to propose the best energy strategies to ensure a secure and sustainable energy transition. The methods of “Levelized cost of energy” (LCOE) and the costs associated with the "engineering process design" allowed to assess the economic feasibility of some scenarios of energy transition identified as interesting for decision making. The current cost of the Cuban electro-energetic system was estimated and compared with the costs obtained for future scenarios simulated. After analyzing the behavior of the indicators in detail, it was identified as the most suitable transition scenario for Cuba, where 150% demand is covered by 90% intermittent energy and 10% wind energy. Also, no backup will be required under these conditions, which represents a considerable saving from the current costs required by an electric generation with fossil resources. The energy storage needs will be 0.05 TWh, and the “concrete towers” and “VOSS” technologies can be used in order to minimize installation and operation costs of these facilities.
François Maréchal, Daniel Alexander Florez Orrego, Meire Ellen Gorete Ribeiro Domingos
François Maréchal, Daniel Alexander Florez Orrego, Meire Ellen Gorete Ribeiro Domingos, Réginald Germanier