A demand system is designed in order to analyze and control the way in which electricity consumption occurs in a scenario, this type of system has four objectives to reduce consumption, reduce costs, reduce peak average to ratio and maximize the comfort of the users. The design of these systems can be based on the implementation of IoT. When using IoT for the development of demand systems, a layer of information is integrated which generates a multiobjective optimization problem. Metaheuristics are used to solve multiobjective problems. This paper introduces a proposed methodology to develop demand systems and the first products implemented.
Many efforts have been made to create scenarios whereby interconnecting IoT can be used. The primary objective of these efforts has been to centralize its access as a single list and to monitor its use and trigger its different functionalities from apps. However, few efforts have addressed the problem of electricity consumption from those devices in the context of a residence. Existing datasets for machine predictive systems are focused on data analytics for global consumption but neglect the use of such solutions by the common citizen as a means of re-educating our citizens and optimizing electricity consumption. Without considering the environmental impact and the urgent need to address this growing global emergency, ordinary citizens require systems that help them be aware of what they consume and thus aspire to make a change. In this work, we propose a methodology that builds on the formal mathematical modeling and development of a simulator to substitute the need to collect real data from real world context of use, as well as an interactive system that integrates the whole process. By adding this module to the architecture our prior work, this work is ready for use in real-life scenarios where electrical consumption could be significantly reduced.
En el presente trabajo se da una breve explicación de la técnica de optimización por cúmulo de partículas para ser implementada como parte de la búsqueda del estado óptimo de consumo de un conjunto de dispositivos. Los dispositivos de uso doméstico, en conjunto, permiten caracterizar el consumo eléctrico de una casa habitación a través del comportamiento de uso. Cada uno de los dispositivos presenta un comportamiento de consumo. El objetivo de la optimización se refleja en la función objetivo, la cual es definida de acuerdo con el propósito general de implementación. Los datos de consumo de los dispositivos eléctricos son almacenados en vectores de consumo-hora, donde cada una de las posiciones corresponde al consumo generado por un dispositivo en una hora determinada. Cada uno de los vectores es usado por la heurística como un vector de referencia durante la búsqueda para encontrar el vector que cumple con la función objetivo.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.