Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/20.500.12421/4506
Title: Algorithms for the Management of Electrical Demand Using a Domotic System with Classification of Electrical Charges
Authors: Suaza Cano, Kevin Andrés
Castillo García, Javier Ferney
Keywords: Demand management
Domotic system
Neural network
Issue Date: 3-Mar-2020
Publisher: Springer
Abstract: Electricity demand management is the process of making appropriate use of energy resources. This process is carried out with the aim of achieving a reduction in electricity consumption. The electrical demand management algorithms are implemented in a domotic system that has the capacity to identify electrical loads using artificial neural networks. An analysis was carried out on the most important physical variables in the home, which have a direct relationship with energy consumption, and strategies were proposed on how to carry out a correct control over these, in search of generating energy savings without affecting comfort levels in the home. It was obtained, as a result that it is possible to generate an energy saving of 63% in comparison to a traditional house, this without affecting to a great extent the comfort of the user and allowing a great level of automation in the home.
URI: http://repository.usc.edu.co/handle/20.500.12421/4506
ISBN: 978-303042519-7
ISSN: 1865-0929
Appears in Collections:Artículos Científicos

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