Optimizing IoT network lifetime through an enhanced hybrid energy harvesting system

[EN] The growing need for sustainable and renewable energy sources has become critical with the Internet of Things (IoT) advancement. IoT relies on low-power, battery-operated devices, but the limited lifespan of these batteries requires frequent recharging or replacement, which is costly and time-c...

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Detalhes bibliográficos
Autores: Rabah, Sirine, Zaier, Aida, Dahman, Hassen, Sendra, Sandra|||0000-0001-9556-9088, Lloret, Jaime|||0000-0002-0862-0533
Tipo de documento: artigo
Data de publicação:2025
País:España
Recursos:Universitat Politècnica de València (UPV)
Repositório:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglês
OAI Identifier:oai:riunet.upv.es:10251/220142
Acesso em linha:https://riunet.upv.es/handle/10251/220142
Access Level:Acceso aberto
Palavra-chave:WSN-IoT
Energy harvesting
Solar
Wind turbine
MPPT
HHO
HBA
Network lifetime
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repository_id_str
spelling Optimizing IoT network lifetime through an enhanced hybrid energy harvesting systemRabah, SirineZaier, AidaDahman, HassenSendra, Sandra|||0000-0001-9556-9088Lloret, Jaime|||0000-0002-0862-0533WSN-IoTEnergy harvestingSolarWind turbineMPPTHHOHBANetwork lifetime[EN] The growing need for sustainable and renewable energy sources has become critical with the Internet of Things (IoT) advancement. IoT relies on low-power, battery-operated devices, but the limited lifespan of these batteries requires frequent recharging or replacement, which is costly and time-consuming. Researchers have proposed energy harvesting systems that capture sustainable ambient energy from the environment to address this issue. This paper presents a hybrid system for harvesting sustainable energy from solar and wind sources. The system features a boost converter controlled by a novel hybrid method combining the Honey Badger Algorithm (HBA) and Harris Hawks Optimization (HHO). This method maximizes power extraction from solar and wind sources, enhancing overall system efficiency. Additionally, the system includes an innovative energy management algorithm that selects the most powerful input source while protecting the storage battery from overcharging or complete depletion, thereby extending its lifespan. The proposed design is validated through MATLAB/Simulink simulations. The HHO-HBA MPPT is compared with existing MPPT methods, evaluating efficiency, battery charge curves, and IoT network energy status. Simulation results show that the proposed approach significantly increases network longevity, offering a cost-effective and sustainable solution for the energy needs of Wireless Sensor Network (WSN)-IoT devices.ElsevierDepartamento de ComunicacionesInstituto de Investigación para la Gestión Integrada de Zonas CosterasEscuela Politécnica Superior de GandiaUniversitat Politècnica de ValènciaRepositorio Institucional de la Universitat Politècnica de València Riunet20252025-01-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/220142reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento - No comercial (by-nc) http://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/2201422026-06-13T07:49:27Z
dc.title.none.fl_str_mv Optimizing IoT network lifetime through an enhanced hybrid energy harvesting system
title Optimizing IoT network lifetime through an enhanced hybrid energy harvesting system
spellingShingle Optimizing IoT network lifetime through an enhanced hybrid energy harvesting system
Rabah, Sirine
WSN-IoT
Energy harvesting
Solar
Wind turbine
MPPT
HHO
HBA
Network lifetime
title_short Optimizing IoT network lifetime through an enhanced hybrid energy harvesting system
title_full Optimizing IoT network lifetime through an enhanced hybrid energy harvesting system
title_fullStr Optimizing IoT network lifetime through an enhanced hybrid energy harvesting system
title_full_unstemmed Optimizing IoT network lifetime through an enhanced hybrid energy harvesting system
title_sort Optimizing IoT network lifetime through an enhanced hybrid energy harvesting system
dc.creator.none.fl_str_mv Rabah, Sirine
Zaier, Aida
Dahman, Hassen
Sendra, Sandra|||0000-0001-9556-9088
Lloret, Jaime|||0000-0002-0862-0533
author Rabah, Sirine
author_facet Rabah, Sirine
Zaier, Aida
Dahman, Hassen
Sendra, Sandra|||0000-0001-9556-9088
Lloret, Jaime|||0000-0002-0862-0533
author_role author
author2 Zaier, Aida
Dahman, Hassen
Sendra, Sandra|||0000-0001-9556-9088
Lloret, Jaime|||0000-0002-0862-0533
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Departamento de Comunicaciones
Instituto de Investigación para la Gestión Integrada de Zonas Costeras
Escuela Politécnica Superior de Gandia
Universitat Politècnica de València
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv WSN-IoT
Energy harvesting
Solar
Wind turbine
MPPT
HHO
HBA
Network lifetime
topic WSN-IoT
Energy harvesting
Solar
Wind turbine
MPPT
HHO
HBA
Network lifetime
description [EN] The growing need for sustainable and renewable energy sources has become critical with the Internet of Things (IoT) advancement. IoT relies on low-power, battery-operated devices, but the limited lifespan of these batteries requires frequent recharging or replacement, which is costly and time-consuming. Researchers have proposed energy harvesting systems that capture sustainable ambient energy from the environment to address this issue. This paper presents a hybrid system for harvesting sustainable energy from solar and wind sources. The system features a boost converter controlled by a novel hybrid method combining the Honey Badger Algorithm (HBA) and Harris Hawks Optimization (HHO). This method maximizes power extraction from solar and wind sources, enhancing overall system efficiency. Additionally, the system includes an innovative energy management algorithm that selects the most powerful input source while protecting the storage battery from overcharging or complete depletion, thereby extending its lifespan. The proposed design is validated through MATLAB/Simulink simulations. The HHO-HBA MPPT is compared with existing MPPT methods, evaluating efficiency, battery charge curves, and IoT network energy status. Simulation results show that the proposed approach significantly increases network longevity, offering a cost-effective and sustainable solution for the energy needs of Wireless Sensor Network (WSN)-IoT devices.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/220142
url https://riunet.upv.es/handle/10251/220142
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial (by-nc)
http://creativecommons.org/licenses/by-nc/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial (by-nc)
http://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869413188182736896
score 15,811543

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