Cuba is traditionally considered a country with an underdeveloped industry. The share of the mining and metallurgical industries in the gross industrial production of the republic is small – about 3 % of GDP. The development of deposits and the extraction of nickel ores is an important sector of the economy of the Republic of Cuba, since the largest reserves of nickel and cobalt on the North American continent are located on the territory of the country. The development of the country energy system can serve as a growth factor in this sector of the economy. Due to climatic features and impossibility of integrating new capacities into the energy system through the construction of hydroelectric power plants, solar energy is a promising direction. Determining the feasibility of using solar tracking systems to increase the generation of electricity from solar power plants is one of the main challenges faced by engineers and renewable energy specialists. Currently, there are no solar tracking systems in Cuba that can provide information to assess the effectiveness of this technology in the country. The lack of the necessary technologies, as well as the high cost of developing solar power plants with tracking systems, limit the widespread introduction of such complexes. Hence follows the task of creating an inexpensive experimental model that allows assessing the effectiveness of tracking systems in specific weather conditions of the Republic of Cuba. This model will allow in future to increase the efficiency of electrical complexes with solar power plants, which provide power supply to the objects of the mineral resource complex and other regions.

The problem of increasing the efficiency of existing power plants is relevant for many countries. Solar power plants built at the end of the 20th century require, as their shelf lives have now expired, not only the replacement of the solar modules, but also the modernization of their component composition. This is due to the requirements to improve the efficiency of power plants to ensure the expansion of renewable energy technologies. This article presents a technical and economic analysis of the choice of solar power plant modernization method, which consists of (1) a method for calculating the amount of power generation; (2) the modeling of solar power plants under specific climatic conditions; (3) the analysis of electricity generation using different types of PV modules and solar radiation trapping technologies in Matlab/Simulink; and (4) the technical and economic analysis of a 2.5 MW solar power plant in the Republic of Cuba (in operation since 2015), for which four different modernization options were considered. All the scenarios differ in the depth of modernization; the results of the analysis were compared with the existing plant. The results of the study showed that the different modernization scenarios respond differently to changes in the inputted technical and economic parameters (cost per kWh, inflation rate, losses, and power plant efficiency). The maximum NPV deviations among the considered scenarios are: a 1% increase in inflation reduces NPV by 2%; a decrease in losses from 20% to 10% increases the NPV by 2.5%; a change in cost from EUR 0.05 to EUR 0.1 increases the NPV by more than 3.5 times. The dependence of the economic results was also tested as a function of three factors: solar module efficiency, inflation, and the price per 1 kWh. It was found that the greatest influence on the NPV of the proposed model is the price per 1 kWh. Based on this analysis, an algorithm was developed to choose the most effective scenario for the conditions of the Republic of Cuba for the modernization of the existing power plants.

This paper presents a computational tool for estimating energy generated by low-power photovoltaic systems based on the specific conditions of the study region since the characteristic energy equation can be obtained considering the main climatological factors affecting these systems in terms of the symmetry or skewness of the random distribution of the generated energy. Furthermore, this paper is aimed at determining any correlation that exists between meteorological variables with respect to the energy generated by 5-kW solar systems in the specific climatic conditions of the Republic of Cuba. The paper also presents the results of the influence of each climate factor on the distribution symmetry of the generated energy of the solar system. Studying symmetry in statistical models is important because they allow us to establish the degree of symmetry (or skewness), which is the probability distribution of a random variable, without having to make a graphical representation of it. Statistical skewness reports the degree to which observations are distributed evenly and proportionally above and below the center (highest) point of the distribution. In the case when the mentioned distribution is balanced, it is called symmetric.