Intelligent Power Management System Using Hybrid Renewable Energy Resources and Decision Tree Approach

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Título: Intelligent Power Management System Using Hybrid Renewable Energy Resources and Decision Tree Approach
Autor/es: Ferrandez-Pastor, Francisco-Javier | Gómez Trillo, Sergio | Nieto-Hidalgo, Mario | García-Chamizo, Juan Manuel | Valdivieso-Sarabia, Rafael J.
Grupo/s de investigación o GITE: Informática Industrial y Redes de Computadores | Grupo de Investigación Interdisciplinar en Docencia Universitaria (GIDU)
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Tecnología Informática y Computación | Universidad de Alicante. Departamento de Didáctica General y Didácticas Específicas
Palabras clave: Smart energy management | Decision tree | Internet of things
Área/s de conocimiento: Arquitectura y Tecnología de Computadores | Didáctica y Organización Escolar
Fecha de publicación: 19-oct-2018
Editor: MDPI
Cita bibliográfica: Ferrández-Pastor F-J, Gómez-Trillo S, Nieto-Hidalgo M, García-Chamizo J-M, Valdivieso-Sarabia R. Intelligent Power Management System Using Hybrid Renewable Energy Resources and Decision Tree Approach. Proceedings. 2018; 2(19):1239. doi:10.3390/proceedings2191239
Resumen: Optimal power usage and consumption require continuous monitoring, forecasting electric energy consumption and renewable generation. To facilitate integration of renewable energies and optimize their resources, new communication and data processing technologies are used in new projects. This article shows the works and results obtained in the eoTICC project. The objective is to design and develop an intelligent energy manager using the Archimedes wind turbine and a solar generation system, both integrated in industrial and residential power facilities. Solutions based on Artificial Intelligence paradigms and Internet of Things protocols allow automatic decision making to optimize energy management. In a facility, the energy demand and weather forecasts can be known by an intelligent energy manager. With these conditions, the energy manager can develop rules based on decision trees to automate control actions aimed at optimizing the use of energy. This article shows the architecture of IoT infrastructure and the first rules designed in the project. The result obtained provides improvements in the use of renewable energy in current facilities that do not use this type of intelligent management. The improvements allow to use the energy at the time of generation, avoiding unnecessary storage.
Patrocinador/es: This research was supported by Industrial Computers and Computer Networks program (I2RC) (2017/2018) funded by the University of Alicante, Wak9 Holding BV company under eo-TICC project and the Valencian Innovation Agency under scientific innovation unit (UCIE Ars Innovatio) of the University of Alicante.
URI: http://hdl.handle.net/10045/82513
ISSN: 2504-3900
DOI: 10.3390/proceedings2191239
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Revisión científica: si
Versión del editor: https://doi.org/10.3390/proceedings2191239
Aparece en las colecciones:INV - I2RC - Artículos de Revistas
INV - GIDU - Artículos de Revistas

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