Publication: Diseñando un gestor de energía de código abierto
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2020-09
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Abstract
La mejora de la eficiencia energética ha sido y es, un tema de fundamental importancia para la industria, el comercio y los gobiernos. Desde hace unos años se está poniendo empeño en lograr un nivel de eficiencia que resulte realmente significativo en todo el mundo y a todo nivel. Para lograrlo, es necesaria la disponibilidad de una herramienta libre y pública de gestión y monitorización de energía, comprendiendo el actual panorama tecnológico y energético. En este trabajo creamos una plataforma web que pretende facilitar este empeño, ofreciendo la información energética a aquellos perfiles de la Universidad Complutense de Madrid que tienen interés en analizar esta información para los diferentes centros en un espacio de tiempo determinado.
La mayoría de ocasiones en las que se necesita realizar estudios energéticos, se requiere observar una comparativa simulando la disposición de energías limpias; en el caso de este proyecto, nos centramos en la opción más viable actualmente, la energía fotovoltaica. El trabajo se separa en tres bloques principales: sección en la que se hace un tratamiento en tiempo real con tecnologías de Big Data de consumo estimado por ocupación de los centros, con sistemas de aviso si ésta comparativa descuadra. Otra sección provee de gráficas con parámetros configurables sobre el uso de energías renovables y cómo afecta al consumo de los centros. Por último, un modelo que predice el consumo energético según el consumo histórico de los centros, con opción de estipular un máximo de ese consumo y disponer de un aviso si ese consumo se podría superar.
The improvement of energy efficiency has been and is, an issue of fundamental importance for industry, commerce and governments. For a few years now, efforts have been made to achieve a level of efficiency that is truly significant worldwide and at all levels. To achieve this, it is necessary to have a free and public tool for managing and monitoring energy, understanding the current technological and energy panorama. In this work we created a web platform that aims to facilitate this effort, offering energy information to those profiles of the Complutense University of Madrid who are interested in analyzing this information for different centers in a given time. Most of the times when energy studies need to be carried out, it is required to observe a comparison simulating the availability of clean energies; in the case of this project, we focus on the most viable option at the moment: photovoltaic energy.The work is separated into three main blocks: section in which a treatment is made in real time with Big Data technologies of estimated consumption by occupation of the centers, with alarm systems if this comparative neglects. Another section provides graphs with configurable parameters on the use of renewable energy and how it affects the consumption of the centers. Finally, a model that predicts energy consumption according to the historical consumption of the centers, with the option of stipulating a maximum of that consumption and having a warning if that consumption could be exceeded.
The improvement of energy efficiency has been and is, an issue of fundamental importance for industry, commerce and governments. For a few years now, efforts have been made to achieve a level of efficiency that is truly significant worldwide and at all levels. To achieve this, it is necessary to have a free and public tool for managing and monitoring energy, understanding the current technological and energy panorama. In this work we created a web platform that aims to facilitate this effort, offering energy information to those profiles of the Complutense University of Madrid who are interested in analyzing this information for different centers in a given time. Most of the times when energy studies need to be carried out, it is required to observe a comparison simulating the availability of clean energies; in the case of this project, we focus on the most viable option at the moment: photovoltaic energy.The work is separated into three main blocks: section in which a treatment is made in real time with Big Data technologies of estimated consumption by occupation of the centers, with alarm systems if this comparative neglects. Another section provides graphs with configurable parameters on the use of renewable energy and how it affects the consumption of the centers. Finally, a model that predicts energy consumption according to the historical consumption of the centers, with the option of stipulating a maximum of that consumption and having a warning if that consumption could be exceeded.
Description
Trabajo de Fin de Máster en Grado en Ingeniería del Software, Facultad de Informática UCM, Departamento de Ingeniería del Software e Inteligencia Artificial, Curso 2019/2020