IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i10p2344-d1393597.html
   My bibliography  Save this article

Tele-Trafficking of Virtual Data Storage Obtained from Smart Grid by Replicated Gluster in Syntose Environment

Author

Listed:
  • Waqas Hashmi

    (Department of Electrical Engineering, Khwaja Fareed University of Engineering & Technology (KFUEIT), Rahim Yar Khan 64200, Pakistan)

  • Shahid Atiq

    (Department of Electrical Engineering, Khwaja Fareed University of Engineering & Technology (KFUEIT), Rahim Yar Khan 64200, Pakistan)

  • Muhammad Majid Hussain

    (School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, UK)

  • Khurram Javed

    (Department of Electrical Engineering, Institute of Space Technology (IST), Islamabad 44000, Pakistan)

Abstract

One of the most important developments in the energy industry is the evolution of smart grids, which record minute details of voltage levels, energy usage, and other critical electrical variables through General Packet Radio Service (GPRS)-enabled meters. This phenomenon creates an extensive dataset for the optimization of the grid system. However, the minute-by-minute energy details recorded by GPRS meters are challenging to store and manage in physical storage resources (old techniques lead to a memory shortage). This study investigates using the distributed file system, replicated Gluster, as a reliable storage option for handling and protecting the enormous volumes of data produced by smart grid components. This study performs two essential tasks. (1) The storage of virtual data received from GPRS meters and load flow analysis of SynerGee Electric 4.0 software from the smart grid (we have extracted electrical data from 16 outgoing feeders, distributed lines, in this manuscript). (2) Tele-trafficking is performed to check the performance of replicated Gluster (RG) for virtual data (electrical data received from the smart grid) storage in terms of User Datagram Protocol (UDP), Transmission Control Protocol (TCP), data flow, and jitter delays. This storage technique provides more opportuni11ty to analyze and perform smart techniques efficiently for future requirement, analysis, and load estimation in smart grids compared to traditional storage methods.

Suggested Citation

  • Waqas Hashmi & Shahid Atiq & Muhammad Majid Hussain & Khurram Javed, 2024. "Tele-Trafficking of Virtual Data Storage Obtained from Smart Grid by Replicated Gluster in Syntose Environment," Energies, MDPI, vol. 17(10), pages 1-31, May.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:10:p:2344-:d:1393597
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/10/2344/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/10/2344/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhou, Bin & Li, Wentao & Chan, Ka Wing & Cao, Yijia & Kuang, Yonghong & Liu, Xi & Wang, Xiong, 2016. "Smart home energy management systems: Concept, configurations, and scheduling strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 30-40.
    2. Jose Ulises Castellanos Contreras & Leonardo Rodríguez Urrego, 2023. "Technological Developments in Control Models Using Petri Nets for Smart Grids: A Review," Energies, MDPI, vol. 16(8), pages 1-21, April.
    3. Zheng, Junjun & Okamura, Hiroyuki & Pang, Taoming & Dohi, Tadashi, 2021. "Availability importance measures of components in smart electric power grid systems," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    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. Flavio Martins & Maria Fatima Almeida & Rodrigo Calili & Agatha Oliveira, 2020. "Design Thinking Applied to Smart Home Projects: A User-Centric and Sustainable Perspective," Sustainability, MDPI, vol. 12(23), pages 1-27, December.
    2. Jia, Kunqi & Guo, Ge & Xiao, Jucheng & Zhou, Huan & Wang, Zhihua & He, Guangyu, 2019. "Data compression approach for the home energy management system," Applied Energy, Elsevier, vol. 247(C), pages 643-656.
    3. Chen, Chien-fei & Nelson, Hannah & Xu, Xiaojing & Bonilla, Gregory & Jones, Nicholas, 2021. "Beyond technology adoption: Examining home energy management systems, energy burdens and climate change perceptions during COVID-19 pandemic," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    4. Ioanna-M. Chatzigeorgiou & Christos Diou & Kyriakos C. Chatzidimitriou & Georgios T. Andreou, 2021. "Demand Response Alert Service Based on Appliance Modeling," Energies, MDPI, vol. 14(10), pages 1-15, May.
    5. Mahmoud H. Elkholy & Tomonobu Senjyu & Mohammed Elsayed Lotfy & Abdelrahman Elgarhy & Nehad S. Ali & Tamer S. Gaafar, 2022. "Design and Implementation of a Real-Time Smart Home Management System Considering Energy Saving," Sustainability, MDPI, vol. 14(21), pages 1-22, October.
    6. Pol Olivella-Rosell & Pau Lloret-Gallego & Íngrid Munné-Collado & Roberto Villafafila-Robles & Andreas Sumper & Stig Ødegaard Ottessen & Jayaprakash Rajasekharan & Bernt A. Bremdal, 2018. "Local Flexibility Market Design for Aggregators Providing Multiple Flexibility Services at Distribution Network Level," Energies, MDPI, vol. 11(4), pages 1-19, April.
    7. Mehrjerdi, Hasan & Bornapour, Mosayeb & Hemmati, Reza & Ghiasi, Seyyed Mohammad Sadegh, 2019. "Unified energy management and load control in building equipped with wind-solar-battery incorporating electric and hydrogen vehicles under both connected to the grid and islanding modes," Energy, Elsevier, vol. 168(C), pages 919-930.
    8. Barbara Kasulaitis & Callie W. Babbitt & Anna Christina Tyler, 2021. "The role of consumer preferences in reducing material intensity of electronic products," Journal of Industrial Ecology, Yale University, vol. 25(2), pages 435-447, April.
    9. Nizami, M.S.H. & Hossain, M.J. & Amin, B.M. Ruhul & Fernandez, Edstan, 2020. "A residential energy management system with bi-level optimization-based bidding strategy for day-ahead bi-directional electricity trading," Applied Energy, Elsevier, vol. 261(C).
    10. Adnan Ahmad & Asif Khan & Nadeem Javaid & Hafiz Majid Hussain & Wadood Abdul & Ahmad Almogren & Atif Alamri & Iftikhar Azim Niaz, 2017. "An Optimized Home Energy Management System with Integrated Renewable Energy and Storage Resources," Energies, MDPI, vol. 10(4), pages 1-35, April.
    11. Correa-Florez, Carlos Adrian & Gerossier, Alexis & Michiorri, Andrea & Kariniotakis, Georges, 2018. "Stochastic operation of home energy management systems including battery cycling," Applied Energy, Elsevier, vol. 225(C), pages 1205-1218.
    12. Prinsloo, Gerro & Dobson, Robert & Mammoli, Andrea, 2018. "Synthesis of an intelligent rural village microgrid control strategy based on smartgrid multi-agent modelling and transactive energy management principles," Energy, Elsevier, vol. 147(C), pages 263-278.
    13. Zhao, Lin-Chuan & Zhou, Teng & Chang, Si-Deng & Zou, Hong-Xiang & Gao, Qiu-Hua & Wu, Zhi-Yuan & Yan, Ge & Wei, Ke-Xiang & Yeatman, Eric M. & Meng, Guang & Zhang, Wen-Ming, 2024. "A disposable cup inspired smart floor for trajectory recognition and human-interactive sensing," Applied Energy, Elsevier, vol. 357(C).
    14. Nuno Rego & Rui Castro & Carlos Santos Silva, 2023. "Assessment of Current Smart House Solutions: The Case of Portugal," Energies, MDPI, vol. 16(22), pages 1-23, November.
    15. K. Yang & Sung-Bae Cho, 2016. "Towards Sustainable Smart Homes by a Hierarchical Hybrid Architecture of an Intelligent Agent," Sustainability, MDPI, vol. 8(10), pages 1-15, October.
    16. Matthew Gough & Sérgio F. Santos & Mohammed Javadi & Rui Castro & João P. S. Catalão, 2020. "Prosumer Flexibility: A Comprehensive State-of-the-Art Review and Scientometric Analysis," Energies, MDPI, vol. 13(11), pages 1-32, May.
    17. Abdelfettah Kerboua & Fouad Boukli-Hacene & Khaldoon A Mourad, 2020. "Particle Swarm Optimization for Micro-Grid Power Management and Load Scheduling," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 71-80.
    18. Krzysztof Gajowniczek & Tomasz Ząbkowski, 2017. "Electricity forecasting on the individual household level enhanced based on activity patterns," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-26, April.
    19. Syed Ali Abbas Kazmi & Muhammad Khuram Shahzad & Akif Zia Khan & Dong Ryeol Shin, 2017. "Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective," Energies, MDPI, vol. 10(4), pages 1-47, April.
    20. Zhang, Ying & Deng, Shuai & Ni, Jiaxin & Zhao, Li & Yang, Xingyang & Li, Minxia, 2017. "A literature research on feasible application of mixed working fluid in flexible distributed energy system," Energy, Elsevier, vol. 137(C), pages 377-390.

    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:17:y:2024:i:10:p:2344-:d:1393597. 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.