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Wide area smart grid architectural model and control: A survey

Author

Listed:
  • Ali, S.M.
  • Jawad, M.
  • Khan, B.
  • Mehmood, C.A.
  • Zeb, N.
  • Tanoli, A.
  • Farid, U.
  • Glower, J.
  • Khan, S.U.

Abstract

The catastrophic outages and time-variant load patterns have posed a complex problem for the energy management policy makers in the deregulated power market. The Wide Area Smart Grid Model (WASGM) is a plausible solution for the future Wide Area Systems (WASs) in terms of the operation, monitoring, and control. This survey provides a comprehensive insight into the state-of-the-art research steered in the wide area control and stability. We present a technical overview of data metering and management classification in the WASs by covering topics, such as: (a) Smart Meters, (b) Smart Sensor Networks, (c) Phasor Measuring Units (PMUs), and (d) Phasor Data Concentrators (PDCs). We also survey the role of Supervisory Control and Data Acquisition (SCADA)/Energy Management System (EMS) in the WASs, to provide a taxonomy of the communication technologies for an efficient data flow in the Smart Grid (SG) network. Moreover, the wide area smart grid architectural model for the future electrical networks is also explored pertaining to the ongoing research in the vast sphere of the WASs. Furthermore, the technical aspects and distinguishing features of the non-linear control schemes utilized for the advanced Wide Area Controls (WACs) are also quantitatively analyzed.

Suggested Citation

  • Ali, S.M. & Jawad, M. & Khan, B. & Mehmood, C.A. & Zeb, N. & Tanoli, A. & Farid, U. & Glower, J. & Khan, S.U., 2016. "Wide area smart grid architectural model and control: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 311-328.
    • Handle: RePEc:eee:rensus:v:64:y:2016:i:c:p:311-328
    DOI: 10.1016/j.rser.2016.06.006
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    References listed on IDEAS

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    1. Unknown, 2016. "Energy for Sustainable Development," Conference Proceedings 253270, Guru Arjan Dev Institute of Development Studies (IDSAsr).
    2. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "A review of residential demand response of smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 166-178.
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    2. Antonio E. Saldaña-González & Andreas Sumper & Mònica Aragüés-Peñalba & Miha Smolnikar, 2020. "Advanced Distribution Measurement Technologies and Data Applications for Smart Grids: A Review," Energies, MDPI, vol. 13(14), pages 1-34, July.
    3. Tu, Chunming & He, Xi & Shuai, Zhikang & Jiang, Fei, 2017. "Big data issues in smart grid – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1099-1107.
    4. Köktürk, G. & Tokuç, A., 2017. "Vision for wind energy with a smart grid in Izmir," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 332-345.
    5. Arcia-Garibaldi, Guadalupe & Cruz-Romero, Pedro & Gómez-Expósito, Antonio, 2018. "Future power transmission: Visions, technologies and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 285-301.
    6. Kolasa, Piotr & Janowski, Mirosław, 2017. "Study of possibilities to store energy virtually in a grid (VESS) with the use of smart metering," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1513-1517.
    7. Alam, Sheraz & Sohail, M. Farhan & Ghauri, Sajjad A. & Qureshi, I.M. & Aqdas, Naveed, 2017. "Cognitive radio based Smart Grid Communication Network," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 535-548.

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