Browsing by Author "Sarmiento Vintimilla, Juan Carlos"

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    Análisis del impacto de la inserción de un sistema de generación distribuida en el alimentador 0427 ubicado en el Complejo Hidroeléctrico Machángara
    (2019-04-26) Cuzco Tenempaguay, Mauro Xavier; Torres Contreras, Santiago Patricio; Sarmiento Vintimilla, Juan Carlos
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    Estudio de la probalidad de pérdida de carga y pérdida de carga horaria para sistemas fotovoltaicos autónomos y/o conectados a la red en Ecuador
    (2016) Altamirano Ortega, Daisy Catalina; Alvarez Cárdenas, Diego Germán; Sarmiento Vintimilla, Juan Carlos
    In this thesis the analysis and evaluation of different methods of sizing of a photovoltaic solar system mainly based on reliability by generating isoreliability lines, and then make a comparison between them and the classical methods are performed. Furthermore, methods are presented to generate radiation data schedules and diaries. The results of these methods are compared with real data and the results of the sizing methods using each of these data are evaluated. The first chapter, discusses the state of art of photovoltaics energy situation, both in the world and in Ecuador, in addition to some definitions of reliability, and a brief description of the used methods. The second chapter, refers to the theoretical framework and the importance of studying the reliability of photovoltaic solar systems, the description of the types of solar photovoltaic systems, its operation and its elements. In the third chapter, some procedures for radiation data generation are exposed, which are used in the methods of sizing photovoltaic systems, then, the procedure for sizing the stand alone and grid connected PV – systems will be displayed. In the fourth chapter, the results of applying each of the sizing methods are exposed, an analysis and comparison of the results are also performed, using real data and data generated. In the fifth and final chapter, the conclusions and recommendations are presented.
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    Estudio de pre-factibilidad para la integración de generación fotovoltaica en el alimentador S-0427 dentro del complejo hidroeléctrico Machángara por parte de la Empresa Electro Generadora del Austro ELECAUSTRO S.A.
    (2019-10-25) Tituana Tituana, Cristian John; Gonzalez Morales, Luis Gerardo; Sarmiento Vintimilla, Juan Carlos
    This thesis shows the pre-feasibility analysis prepared in covenant with the Company Empresa Electro Generadora del Austro. This analysis is applied to the Complejo Hidroeléctrico Machángara where areas with sufficient properties for the integration of photovoltaic designs were determined through exploration. In addition, pre-feasibility level designs corresponding to each area are made for technical and economic evaluation. From the establishment of useful areas for photovoltaic generation and different alternatives of technical design at the prefeasibility level, the technical analysis and economic analysis are carried out under different financing scenarios. As a result, the necessary approximate budget, the average cost of energy production and the existence of pre-feasibility for the delimited sector are obtained. Finally, the existence of technical and economic pre-feasibility for the integration of photovoltaic generation for the Saucay, Dutasay and Labrado sectors was determined. Result obtained by determining the financing and technical design scenario that offers the highest cost-benefit ratio corresponding to each area.
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    Metodología para determinar el precio de comercialización de la energía producida por una central fotovoltaica conectada a la red
    (2016) Herrera Molina, Santiago Martin; Sarmiento Vintimilla, Juan Carlos
    Given de boom of renewable energy around the world, as an alternative solution to reducing the greenhouse gases, in the fight against the climate change, this research proposes a methodology detailing the need for pre-feasibility study of a photovoltaic plant.To do this, first the legal frameworkunder which the functioning and operation of these plants referred to in Ecuador is analyzed. The methodology is based on two analyzes; one concerning the technical calculation of the size of photovoltaic systems connected to the electric grid, and another focused on the economic evaluation of the project, to determinate a selling process of energy, that is profitable on investment. In the development of this thesis applied technical and economic criteria of reality of Ecuador´s electricity sector are presented. For this study a photovoltaic generation project arises whit real information from the weather station owned by the company ELECAUSTRO S.A. Quotes applied to both domestic and international manufactures and suppliers of all materials and equipment needed for installation. Administration, operation and maintenance are also estimated with reference to a plant of similar capacity. This information could be established several cases of financing with different prices energy trading, thus obtaining a specific proposal for the casestudy.
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    Predicting ozone pollution in urban areas using machine learning and quantile regression models
    (Springer International Publishing, 2021) Cueva, Fernando; Saquicela Galarza, Víctor Hugo; Sarmiento Vintimilla, Juan Carlos; Cabrera Mejia, Fanny Virginia; Sarmiento Jara, Juan Pablo; Sarmiento Jara, Juan Pablo
    Ozone is the most harmful secondary pollutant in terms of negative effects on climate change and human health. Predicting ozone emission levels has therefore gained importance within the field of environmental management. This study, performed in the Andean city of Cuenca, Ecuador, compares the performance of two methodologies currently used for this task and based on machine learning and quantile regression techniques. These techniques were applied using cross-sectional data to predict the ozone concentration per city block during the year 2018. Our results reveal that ozone concentration is significantly influenced by nitrogen dioxide, sedimentary particles, sulfur dioxide, traffic, and spatial features. We use the mean square error, the coefficient of determination, and the quantile loss as evaluation metrics for the performance of the ozone prediction models, employing a cross-validation scheme with a fold. Our work shows that the random forest technique outperforms gradient boosting prediction, neural network, and quantile regression methods.