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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
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    References listed on IDEAS

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    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. 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).
    3. 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.
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