IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i13p10252-d1181771.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/13/10252/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/13/10252/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    2. 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.
    3. Ahmed Hussain Elmetwaly & Ramy Adel Younis & Abdelazeem Abdallah Abdelsalam & Ahmed Ibrahim Omar & Mohamed Metwally Mahmoud & Faisal Alsaif & Adel El-Shahat & Mohamed Attya Saad, 2023. "Modeling, Simulation, and Experimental Validation of a Novel MPPT for Hybrid Renewable Sources Integrated with UPQC: An Application of Jellyfish Search Optimizer," Sustainability, MDPI, vol. 15(6), pages 1-30, March.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yao, Ganzhou & Luo, Zirong & Lu, Zhongyue & Wang, Mangkuan & Shang, Jianzhong & Guerrerob, Josep M., 2023. "Unlocking the potential of wave energy conversion: A comprehensive evaluation of advanced maximum power point tracking techniques and hybrid strategies for sustainable energy harvesting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    2. Haoming Liu & Muhammad Yasir Ali Khan & Xiaoling Yuan, 2023. "Hybrid Maximum Power Extraction Methods for Photovoltaic Systems: A Comprehensive Review," Energies, MDPI, vol. 16(15), pages 1-64, July.
    3. Ehtisham Lodhi & Fei-Yue Wang & Gang Xiong & Ghulam Ali Mallah & Muhammad Yaqoob Javed & Tariku Sinshaw Tamir & David Wenzhong Gao, 2021. "A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems," Sustainability, MDPI, vol. 13(19), pages 1-27, September.
    4. Priya, K. & Sathishkumar, K. & Rajasekar, N., 2018. "A comprehensive review on parameter estimation techniques for Proton Exchange Membrane fuel cell modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 121-144.
    5. Ping Jiang & Tianyi Zhang & Jinpeng Geng & Peiguang Wang & Lei Fu, 2023. "An MPPT Strategy for Wind Turbines Combining Feedback Linearization and Model Predictive Control," Energies, MDPI, vol. 16(10), pages 1-16, May.
    6. Mariam A. Sameh & Mostafa I. Marei & M. A. Badr & Mahmoud A. Attia, 2021. "An Optimized PV Control System Based on the Emperor Penguin Optimizer," Energies, MDPI, vol. 14(3), pages 1-16, February.
    7. Lin Sun & Suisui Chen & Jiucheng Xu & Yun Tian, 2019. "Improved Monarch Butterfly Optimization Algorithm Based on Opposition-Based Learning and Random Local Perturbation," Complexity, Hindawi, vol. 2019, pages 1-20, February.
    8. Kumar Ganti, Praful & Naik, Hrushikesh & Kanungo Barada, Mohanty, 2022. "Environmental impact analysis and enhancement of factors affecting the photovoltaic (PV) energy utilization in mining industry by sparrow search optimization based gradient boosting decision tree appr," Energy, Elsevier, vol. 244(PA).
    9. Pillai, Dhanup S. & Rajasekar, N., 2018. "Metaheuristic algorithms for PV parameter identification: A comprehensive review with an application to threshold setting for fault detection in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3503-3525.
    10. Yashar Mousavi & Geraint Bevan & Ibrahim Beklan Küçükdemiral & Afef Fekih, 2021. "Maximum Power Extraction from Wind Turbines Using a Fault-Tolerant Fractional-Order Nonsingular Terminal Sliding Mode Controller," Energies, MDPI, vol. 14(18), pages 1-16, September.
    11. Hussain A. Alhaiz & Ahmed S. Alsafran & Ali H. Almarhoon, 2023. "Single-Phase Microgrid Power Quality Enhancement Strategies: A Comprehensive Review," Energies, MDPI, vol. 16(14), pages 1-28, July.
    12. Ritwik Haldar & Ashraf Hossain & Kirtan Gopal Panda, 2019. "Estimation of event loss duration for energy harvested wireless body sensor node," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 70(2), pages 231-244, February.
    13. Prasanth Ram, J. & Rajasekar, N., 2017. "A new robust, mutated and fast tracking LPSO method for solar PV maximum power point tracking under partial shaded conditions," Applied Energy, Elsevier, vol. 201(C), pages 45-59.
    14. González-Hernández, José Genaro & Salas-Cabrera, Rubén & Vázquez-Bautista, Roberto & Ong-de-la-Cruz, Luis Manuel & Rodríguez-Guillén, Joel, 2021. "A novel MPPT PI discrete reverse-acting controller for a wind energy conversion system," Renewable Energy, Elsevier, vol. 178(C), pages 904-915.
    15. Osmani, Khaled & Haddad, Ahmad & Lemenand, Thierry & Castanier, Bruno & Ramadan, Mohamad, 2021. "An investigation on maximum power extraction algorithms from PV systems with corresponding DC-DC converters," Energy, Elsevier, vol. 224(C).
    16. Ram, J. Prasanth & Manghani, Himanshu & Pillai, Dhanup S. & Babu, T. Sudhakar & Miyatake, Masafumi & Rajasekar, N., 2018. "Analysis on solar PV emulators: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 149-160.
    17. Poompavai, T. & Kowsalya, M., 2019. "Control and energy management strategies applied for solar photovoltaic and wind energy fed water pumping system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 108-122.
    18. José Genaro González-Hernández & Rubén Salas-Cabrera, 2021. "Wind Power Extraction Optimization by Dynamic Gain Scheduling Approximation Based on Non-Linear Functions for a WECS Based on a PMSG," Mathematics, MDPI, vol. 9(17), pages 1-19, August.
    19. Dai, Juchuan & Tan, Yayi & Shen, Xiangbin, 2019. "Investigation of energy output in mountain wind farm using multiple-units SCADA data," Applied Energy, Elsevier, vol. 239(C), pages 225-238.
    20. Aliyu Sabo & Bashir Yunus Kolapo & Theophilus Ebuka Odoh & Musa Dyari & Noor Izzri Abdul Wahab & Veerapandiyan Veerasamy, 2022. "Solar, Wind and Their Hybridization Integration for Multi-Machine Power System Oscillation Controllers Optimization: A Review," Energies, MDPI, vol. 16(1), pages 1-32, December.

    More about this item

    Keywords

    IoT; energy harvesting; PV; WT; SEPIC; PSO; HHO;
    All these keywords.

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10252-:d:1181771. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.