IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i9p3860-d1137643.html
   My bibliography  Save this article

IoT-Based Low-Cost Photovoltaic Monitoring for a Greenhouse Farm in an Arid Region

Author

Listed:
  • Amor Hamied

    (Renewable Energy Laboratory, Faculty of Sciences and Technology, Departement of Electronics, University of Jijel, Jijel 18000, Algeria)

  • Adel Mellit

    (Renewable Energy Laboratory, Faculty of Sciences and Technology, Departement of Electronics, University of Jijel, Jijel 18000, Algeria)

  • Mohamed Benghanem

    (Department of Physics, Faculty of Science, Islamic University of Madinah, Madinah 42351, Saudi Arabia)

  • Sahbi Boubaker

    (Department of Computer and Network Engineering, College of Computer Science and Engineering, University of Jeddah, Jeddah 21959, Saudi Arabia)

Abstract

In this paper, a low-cost monitoring system for an off-grid photovoltaic (PV) system, installed at an isolated location (Sahara region, south of Algeria), is designed. The PV system is used to supply a small-scale greenhouse farm. A simple and accurate fault diagnosis algorithm was developed and integrated into a low-cost microcontroller for real time validation. The monitoring system, including the fault diagnosis procedure, was evaluated under specific climate conditions. The Internet of Things (IoT) technique is used to remotely monitor the data, such as PV currents, PV voltages, solar irradiance, and cell temperature. A friendly web page was also developed to visualize the data and check the state of the PV system remotely. The users could be notified about the state of the PV system via phone SMS. Results showed that the system performs better under this climate conditions and that it can supply the considered greenhouse farm. It was also shown that the integrated algorithm is able to detect and identify some examined defects with a good accuracy. The total cost of the designed IoT-based monitoring system is around 73 euros and its average energy consumed per day is around 13.5 Wh.

Suggested Citation

  • Amor Hamied & Adel Mellit & Mohamed Benghanem & Sahbi Boubaker, 2023. "IoT-Based Low-Cost Photovoltaic Monitoring for a Greenhouse Farm in an Arid Region," Energies, MDPI, vol. 16(9), pages 1-21, April.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:9:p:3860-:d:1137643
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/9/3860/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/9/3860/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wiesinger, F. & Sutter, F. & Fernández-García, A. & Wette, J. & Hanrieder, N., 2021. "Sandstorm erosion on solar reflectors: A field study on height and orientation dependence," Energy, Elsevier, vol. 217(C).
    2. Mussawir Ul Mehmood & Abasin Ulasyar & Waleed Ali & Kamran Zeb & Haris Sheh Zad & Waqar Uddin & Hee-Je Kim, 2023. "A New Cloud-Based IoT Solution for Soiling Ratio Measurement of PV Systems Using Artificial Neural Network," Energies, MDPI, vol. 16(2), pages 1-14, January.
    3. Alshawaf, Mohammad & Poudineh, Rahmatallah & Alhajeri, Nawaf S., 2020. "Solar PV in Kuwait: The effect of ambient temperature and sandstorms on output variability and uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    4. Adel Mellit & Mohamed Benghanem & Omar Herrak & Abdelaziz Messalaoui, 2021. "Design of a Novel Remote Monitoring System for Smart Greenhouses Using the Internet of Things and Deep Convolutional Neural Networks," Energies, MDPI, vol. 14(16), pages 1-16, August.
    5. Masoud Emamian & Aref Eskandari & Mohammadreza Aghaei & Amir Nedaei & Amirmohammad Moradi Sizkouhi & Jafar Milimonfared, 2022. "Cloud Computing and IoT Based Intelligent Monitoring System for Photovoltaic Plants Using Machine Learning Techniques," Energies, MDPI, vol. 15(9), pages 1-25, April.
    6. Koutroulis, Eftichios & Kalaitzakis, Kostas, 2003. "Development of an integrated data-acquisition system for renewable energy sources systems monitoring," Renewable Energy, Elsevier, vol. 28(1), pages 139-152.
    7. Abdulsalam S. Alghamdi & AbuBakr S. Bahaj & Luke S. Blunden & Yue Wu, 2019. "Dust Removal from Solar PV Modules by Automated Cleaning Systems," Energies, MDPI, vol. 12(15), pages 1-21, July.
    8. José Miguel Paredes-Parra & Antonio Javier García-Sánchez & Antonio Mateo-Aroca & Ángel Molina-García, 2019. "An Alternative Internet-of-Things Solution Based on LoRa for PV Power Plants: Data Monitoring and Management," Energies, MDPI, vol. 12(5), pages 1-20, March.
    9. Mellit, Adel & Kalogirou, Soteris, 2021. "Artificial intelligence and internet of things to improve efficacy of diagnosis and remote sensing of solar photovoltaic systems: Challenges, recommendations and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    10. Mohamed Benghanem & Adel Mellit & Mohammed Emad & Abdulaziz Aljohani, 2021. "Monitoring of Solar Still Desalination System Using the Internet of Things Technique," Energies, MDPI, vol. 14(21), pages 1-12, October.
    Full references (including those not matched with items on IDEAS)

    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. Mellit, A. & Benghanem, M. & Kalogirou, S. & Massi Pavan, A., 2023. "An embedded system for remote monitoring and fault diagnosis of photovoltaic arrays using machine learning and the internet of things," Renewable Energy, Elsevier, vol. 208(C), pages 399-408.
    2. Francisco José Gimeno-Sales & Salvador Orts-Grau & Alejandro Escribá-Aparisi & Pablo González-Altozano & Ibán Balbastre-Peralta & Camilo Itzame Martínez-Márquez & María Gasque & Salvador Seguí-Chilet, 2020. "PV Monitoring System for a Water Pumping Scheme with a Lithium-Ion Battery Using Free Open-Source Software and IoT Technologies," Sustainability, MDPI, vol. 12(24), pages 1-28, December.
    3. Tang, Wuqin & Yang, Qiang & Dai, Zhou & Yan, Wenjun, 2024. "Module defect detection and diagnosis for intelligent maintenance of solar photovoltaic plants: Techniques, systems and perspectives," Energy, Elsevier, vol. 297(C).
    4. Daiva Stanelyte & Neringa Radziukyniene & Virginijus Radziukynas, 2022. "Overview of Demand-Response Services: A Review," Energies, MDPI, vol. 15(5), pages 1-31, February.
    5. Gad, H.E. & Gad, Hisham E., 2015. "Development of a new temperature data acquisition system for solar energy applications," Renewable Energy, Elsevier, vol. 74(C), pages 337-343.
    6. Wu, Yubo & Du, Jianqiang & Liu, Guangxin & Ma, Danzhu & Jia, Fengrui & Klemeš, Jiří Jaromír & Wang, Jin, 2022. "A review of self-cleaning technology to reduce dust and ice accumulation in photovoltaic power generation using superhydrophobic coating," Renewable Energy, Elsevier, vol. 185(C), pages 1034-1061.
    7. Rocio Camarena-Martinez & Rocio A. Lizarraga-Morales & Roberto Baeza-Serrato, 2021. "Classification of Geomembranes as Raw Material for Defects Reduction in the Manufacture of Biodigesters Using an Artificial Neuronal Network," Energies, MDPI, vol. 14(21), pages 1-13, November.
    8. Abolfazl Shiroudi & Seyed Taklimi & Seyed Mousavifar & Peyman Taghipour, 2013. "Stand-alone PV-hydrogen energy system in Taleghan-Iran using HOMER software: optimization and techno-economic analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 15(5), pages 1389-1402, October.
    9. Guillermo Almonacid-Olleros & Gabino Almonacid & David Gil & Javier Medina-Quero, 2022. "Evaluation of Transfer Learning and Fine-Tuning to Nowcast Energy Generation of Photovoltaic Systems in Different Climates," Sustainability, MDPI, vol. 14(5), pages 1-15, March.
    10. Yap, Kah Yung & Chin, Hon Huin & Klemeš, Jiří Jaromír, 2022. "Solar Energy-Powered Battery Electric Vehicle charging stations: Current development and future prospect review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    11. Mariusz T. Sarniak, 2020. "Researches of the Impact of the Nominal Power Ratio and Environmental Conditions on the Efficiency of the Photovoltaic System: A Case Study for Poland in Central Europe," Sustainability, MDPI, vol. 12(15), pages 1-15, July.
    12. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    13. Mohd Nasir Ayob & Valeria Castellucci & Johan Abrahamsson & Rafael Waters, 2019. "A Remotely Controlled Sea Level Compensation System for Wave Energy Converters," Energies, MDPI, vol. 12(10), pages 1-16, May.
    14. Hong, Ying-Yi & Pula, Rolando A., 2022. "Detection and classification of faults in photovoltaic arrays using a 3D convolutional neural network," Energy, Elsevier, vol. 246(C).
    15. Adel Mellit & Chadia Zayane & Sahbi Boubaker & Souad Kamel, 2023. "A Sustainable Fault Diagnosis Approach for Photovoltaic Systems Based on Stacking-Based Ensemble Learning Methods," Mathematics, MDPI, vol. 11(4), pages 1-15, February.
    16. Rimantas Barauskas & Andrius Kriščiūnas & Dalia Čalnerytė & Paulius Pilipavičius & Tautvydas Fyleris & Vytautas Daniulaitis & Robertas Mikalauskis, 2022. "Approach of AI-Based Automatic Climate Control in White Button Mushroom Growing Hall," Agriculture, MDPI, vol. 12(11), pages 1-25, November.
    17. Villasevil, F. Xavier & Vigara, Julio E. & Chiarle, Lautaro, 2013. "Plug-in driven architecture for renewable energy generation monitoring," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 401-406.
    18. Faris E. Alfaris, 2023. "A Sensorless Intelligent System to Detect Dust on PV Panels for Optimized Cleaning Units," Energies, MDPI, vol. 16(3), pages 1-17, January.
    19. Marta Redondo & Carlos A. Platero & Antonio Moset & Fernando Rodríguez & Vicente Donate, 2023. "Soiling Modelling in Large Grid-Connected PV Plants for Cleaning Optimization," Energies, MDPI, vol. 16(2), pages 1-13, January.
    20. Armin Razmjoo & Arezoo Ghazanfari & Poul Alberg Østergaard & Sepideh Abedi, 2023. "Design and Analysis of Grid-Connected Solar Photovoltaic Systems for Sustainable Development of Remote Areas," Energies, MDPI, vol. 16(7), pages 1-21, March.

    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:jeners:v:16:y:2023:i:9:p:3860-:d:1137643. 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.