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Efficiency Enhancement of a Hybrid Sustainable Energy Harvesting System Using HHHOPSO-MPPT for IoT Devices

Author

Listed:
  • Sirine Rabah

    (MACS Laboratory LR 16ES22, National Engineering School of Gabes, University of Gabes, Omar ibn Elkhattab Street, Zrig Eddakhlania 6029, Tunisia)

  • Aida Zaier

    (LR-11/TIC-03 Innov’COM Laboratory, Higher School of Communication of Tunis, University of Carthage, Ariana 2083, Tunisia)

  • Jaime Lloret

    (Instituto de Investigacion para la Gestion Integrada de Zonas Costeras, Universitat Politecnica de Valencia, 46730 Gandia, Spain)

  • Hassen Dahman

    (LaPhyMNE Laboratory (LR05ES14), FS Gabes, University of Gabes, Gabes 6029, Tunisia
    Department of Electrical Engineering, National Engineering School of Gabes, University of Gabes, Gabes 6029, Tunisia)

Abstract

The Internet of Things (IoT) is a network of interconnected physical devices, vehicles, and buildings that are embedded with sensors, software, and network connectivity, enabling them to collect and exchange data. This exchange of data between the physical and digital worlds allows for a wide range of applications, from smart homes and cities to industrial automation and healthcare. However, a key challenge faced by IoT nodes is the limited availability of energy to support their operations. Typically, these nodes can only function for a few days based on their duty cycle. This paper introduces a solution that aims to ensure the sustainability of IoT applications by addressing this energy challenge. Thus, we develop a design of a hybrid sustainable energy system designed specifically for IoT nodes, using solar photovoltaic (PV) and wind turbines (WT) chosen for their multiple benefits and complementarity. The system uses the single-ended primary-inductance converter (SEPIC) and is controlled using a hybrid approach, combining Harris Hawks Optimization and Particle Swarm Optimization (HHHOPSO). Each SEPIC converter boost the electrical energy generated to attain the required voltage level when charging the battery. The proposed methodology is implemented in MATLAB/Simulink and its performance is measured using appropriate metrics. In terms of efficiency and average power, the results show that the suggested method outperforms previous strategies. Our system powers also many sensor nodes, leading to a high level of sustainability and lowering the carbon footprint associated with traditional energy sources.

Suggested Citation

  • Sirine Rabah & Aida Zaier & Jaime Lloret & Hassen Dahman, 2023. "Efficiency Enhancement of a Hybrid Sustainable Energy Harvesting System Using HHHOPSO-MPPT for IoT Devices," Sustainability, MDPI, vol. 15(13), pages 1-28, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10252-:d:1181771
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    References listed on IDEAS

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    1. Mokhtari, Yacine & Rekioua, Djamila, 2018. "High performance of Maximum Power Point Tracking Using Ant Colony algorithm in wind turbine," Renewable Energy, Elsevier, vol. 126(C), pages 1055-1063.
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    3. Ram, J.Prasanth & Rajasekar, N. & Miyatake, Masafumi, 2017. "Design and overview of maximum power point tracking techniques in wind and solar photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1138-1159.
    4. Salar Chamanian & Sajjad Baghaee & Hasan Ulusan & Özge Zorlu & Haluk Külah & Elif Uysal-Biyikoglu, 2014. "Powering-up Wireless Sensor Nodes Utilizing Rechargeable Batteries and an Electromagnetic Vibration Energy Harvesting System," Energies, MDPI, vol. 7(10), pages 1-17, October.
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    Cited by:

    1. Mohammed Yousri Silaa & Oscar Barambones & José Antonio Cortajarena & Patxi Alkorta & Aissa Bencherif, 2023. "PEMFC Current Control Using a Novel Compound Controller Enhanced by the Black Widow Algorithm: A Comprehensive Simulation Study," Sustainability, MDPI, vol. 15(18), pages 1-23, September.

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    More about this item

    Keywords

    IoT; energy harvesting; PV; WT; SEPIC; PSO; HHO;
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