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Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System
Integration of vehicle-to-home (V2H) centralized photovoltaic (HCPV) systems is a requested and potentially fruitful research topic for both industry and academia. Renewable energy sources, such as wind turbines and solar photovoltaic panels, alleviate energy deficits. Furthermore, energy storage te...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9656865/ https://www.ncbi.nlm.nih.gov/pubmed/36365841 http://dx.doi.org/10.3390/s22218142 |
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author | Almughram, Ohoud Ben Slama, Sami Zafar, Bassam |
author_facet | Almughram, Ohoud Ben Slama, Sami Zafar, Bassam |
author_sort | Almughram, Ohoud |
collection | PubMed |
description | Integration of vehicle-to-home (V2H) centralized photovoltaic (HCPV) systems is a requested and potentially fruitful research topic for both industry and academia. Renewable energy sources, such as wind turbines and solar photovoltaic panels, alleviate energy deficits. Furthermore, energy storage technologies, such as batteries, thermal, and electric vehicles, are indispensable. Consequently, in this article, we examine the impact of solar photovoltaic (SPV), microgrid (MG) storage, and an electric vehicle (EV) on maximum sun radiation hours. As a result, an HCPV scheduling algorithm is developed and applied to maximize energy sustainability in a smart home (SH). The suggested algorithm can manage energy demand between the MG and SPV systems, as well as the EV as a mobile storage system. The model is based on several limitations to meet households’ electrical needs during sunny and cloudy weather. A multi-agent system (MAS) is undertaken to ensure proper system operation and meet the power requirements of various devices. An experimental database for weather and appliances is deployed to evaluate and control energy consumption and production cost parameters. The obtained results illustrate the benefits of V2H technology as a prospective unit storage solution. |
format | Online Article Text |
id | pubmed-9656865 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96568652022-11-15 Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System Almughram, Ohoud Ben Slama, Sami Zafar, Bassam Sensors (Basel) Article Integration of vehicle-to-home (V2H) centralized photovoltaic (HCPV) systems is a requested and potentially fruitful research topic for both industry and academia. Renewable energy sources, such as wind turbines and solar photovoltaic panels, alleviate energy deficits. Furthermore, energy storage technologies, such as batteries, thermal, and electric vehicles, are indispensable. Consequently, in this article, we examine the impact of solar photovoltaic (SPV), microgrid (MG) storage, and an electric vehicle (EV) on maximum sun radiation hours. As a result, an HCPV scheduling algorithm is developed and applied to maximize energy sustainability in a smart home (SH). The suggested algorithm can manage energy demand between the MG and SPV systems, as well as the EV as a mobile storage system. The model is based on several limitations to meet households’ electrical needs during sunny and cloudy weather. A multi-agent system (MAS) is undertaken to ensure proper system operation and meet the power requirements of various devices. An experimental database for weather and appliances is deployed to evaluate and control energy consumption and production cost parameters. The obtained results illustrate the benefits of V2H technology as a prospective unit storage solution. MDPI 2022-10-24 /pmc/articles/PMC9656865/ /pubmed/36365841 http://dx.doi.org/10.3390/s22218142 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Almughram, Ohoud Ben Slama, Sami Zafar, Bassam Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System |
title | Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System |
title_full | Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System |
title_fullStr | Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System |
title_full_unstemmed | Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System |
title_short | Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System |
title_sort | model for managing the integration of a vehicle-to-home unit into an intelligent home energy management system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9656865/ https://www.ncbi.nlm.nih.gov/pubmed/36365841 http://dx.doi.org/10.3390/s22218142 |
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