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A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy

Contrary to the rapid evolution experienced in the last decade of Information and Communication Technologies and particularly the Internet of Things, electric power distribution systems have remained exceptionally steady for a long time. Energy users are no longer passive actors; the prosumer is exp...

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Autores principales: Caballero, Víctor, Vernet, David, Zaballos, Agustín
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374439/
https://www.ncbi.nlm.nih.gov/pubmed/32630750
http://dx.doi.org/10.3390/s20133704
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author Caballero, Víctor
Vernet, David
Zaballos, Agustín
author_facet Caballero, Víctor
Vernet, David
Zaballos, Agustín
author_sort Caballero, Víctor
collection PubMed
description Contrary to the rapid evolution experienced in the last decade of Information and Communication Technologies and particularly the Internet of Things, electric power distribution systems have remained exceptionally steady for a long time. Energy users are no longer passive actors; the prosumer is expected to be the primary agent in the Future Grid. Demand Side Management refers to the management of energy production and consumption at the demand side, and there seems to be an increasing concern about the scalability of Demand Side Management services. The creation of prosumer communities leveraging the Smart Grid to improve energy production and consumption patterns has been proposed in the literature, and several works concerned with scalability of Demand Side Management services group prosumers to improve Demand Side Management services scalability. In our previous work, we coin the term Social Internet of Energy to refer to the integration between devices, prosumers and groups of prosumers via social relationships. In this work, we develop an algorithm to coordinate the different clusters we create using the clustering method by load profile compatibility (instead of similarity). Our objective is to explore the possibilities of the cluster-by-compatibility heuristic we proposed in our previous work. We perform experiments using synthetic and real datasets. Results show that we can obtain a global reduction in Peak-to-Average Ratio with datasets containing up to 200 rosumers and creating up to 6 Prosumer Community Groups, and imply that those Prosumer Community Groups can perform load rescheduling semi-autonomously and in parallel with each other.
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spelling pubmed-73744392020-08-06 A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy Caballero, Víctor Vernet, David Zaballos, Agustín Sensors (Basel) Article Contrary to the rapid evolution experienced in the last decade of Information and Communication Technologies and particularly the Internet of Things, electric power distribution systems have remained exceptionally steady for a long time. Energy users are no longer passive actors; the prosumer is expected to be the primary agent in the Future Grid. Demand Side Management refers to the management of energy production and consumption at the demand side, and there seems to be an increasing concern about the scalability of Demand Side Management services. The creation of prosumer communities leveraging the Smart Grid to improve energy production and consumption patterns has been proposed in the literature, and several works concerned with scalability of Demand Side Management services group prosumers to improve Demand Side Management services scalability. In our previous work, we coin the term Social Internet of Energy to refer to the integration between devices, prosumers and groups of prosumers via social relationships. In this work, we develop an algorithm to coordinate the different clusters we create using the clustering method by load profile compatibility (instead of similarity). Our objective is to explore the possibilities of the cluster-by-compatibility heuristic we proposed in our previous work. We perform experiments using synthetic and real datasets. Results show that we can obtain a global reduction in Peak-to-Average Ratio with datasets containing up to 200 rosumers and creating up to 6 Prosumer Community Groups, and imply that those Prosumer Community Groups can perform load rescheduling semi-autonomously and in parallel with each other. MDPI 2020-07-02 /pmc/articles/PMC7374439/ /pubmed/32630750 http://dx.doi.org/10.3390/s20133704 Text en © 2020 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/).
spellingShingle Article
Caballero, Víctor
Vernet, David
Zaballos, Agustín
A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy
title A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy
title_full A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy
title_fullStr A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy
title_full_unstemmed A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy
title_short A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy
title_sort heuristic to create prosumer community groups in the social internet of energy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374439/
https://www.ncbi.nlm.nih.gov/pubmed/32630750
http://dx.doi.org/10.3390/s20133704
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