IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i12p3245-d375172.html
   My bibliography  Save this article

A Review of Cognitive Radio Smart Grid Communication Infrastructure Systems

Author

Listed:
  • Daisy Nkele Molokomme

    (Department of Electrical and Electronic Engineering Technology, University of Johannesburg, Johannesburg 2028, South Africa)

  • Chabalala S. Chabalala

    (School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg 2050, South Africa)

  • Pitshou N. Bokoro

    (Department of Electrical and Electronic Engineering Technology, University of Johannesburg, Johannesburg 2028, South Africa)

Abstract

The cognitive smart grid (SG) communication paradigm aims to mitigate quality of service (QoS) issues in obsolete communication architecture associated with the conventional electrical grid. This paradigm entails the integration of advanced information and communication technologies (ICTs) into power grids, enabling a two-way flow of information. However, due to the exponential increase in wireless applications and services, also driven by the deployment of the Internet of Things (IoT) smart devices, SG communication systems are expected to handle large volumes of data. As a result, the operation of SG networks is confronted with the major challenge of managing and processing data in a reliable and secure manner. The existing works in the literature proposed architectures with the objective to mitigate the underlying QoS issues such as latency, bandwidth, data congestion, energy efficiency, etc. In addition, a variety of communication technologies have been analyzed for their capacity to support stringent QoS requirements for diverse SGs environments. This notwithstanding, a standard architecture designed to mitigate the aforementioned issues for SG networks remains a work-in-progress. The main objective of this paper is to investigate the emerging technologies such as cognitive radio networks (CRNs) as part of the Fifth-Generation (5G) mobile technology for reliable communication in SG networks. Furthermore, a hybrid architecture based on the combination of fog computing and cloud computing is proposed. In this architecture, real-time latency-sensitive information is given high priority, with fog edge based servers deployed in close proximity to home area networks (HANs) for preprocessing and analyzing of information collected from smart IoT devices. In comparison to the recent works in the literature, which are mainly based on CRNs and 5G separately, the proposed architecture in this paper incorporates the combination of CRNs and 5G for reliable and efficient communication in SG networks.

Suggested Citation

  • Daisy Nkele Molokomme & Chabalala S. Chabalala & Pitshou N. Bokoro, 2020. "A Review of Cognitive Radio Smart Grid Communication Infrastructure Systems," Energies, MDPI, vol. 13(12), pages 1-20, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3245-:d:375172
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/12/3245/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/12/3245/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sofana Reka. S & Tomislav Dragičević & Pierluigi Siano & S.R. Sahaya Prabaharan, 2019. "Future Generation 5G Wireless Networks for Smart Grid: A Comprehensive Review," Energies, MDPI, vol. 12(11), pages 1-17, June.
    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. Yousaf Murtaza Rind & Muhammad Haseeb Raza & Muhammad Zubair & Muhammad Qasim Mehmood & Yehia Massoud, 2023. "Smart Energy Meters for Smart Grids, an Internet of Things Perspective," Energies, MDPI, vol. 16(4), pages 1-35, February.
    2. Daisy Nkele Molokomme & Chabalala S. Chabalala & Pitshou N. Bokoro, 2021. "Enhancement of Advanced Metering Infrastructure Performance Using Unsupervised K-Means Clustering Algorithm," Energies, MDPI, vol. 14(9), pages 1-14, May.
    3. Miroslaw Parol & Jacek Wasilewski & Tomasz Wojtowicz & Bartlomiej Arendarski & Przemyslaw Komarnicki, 2022. "Reliability Analysis of MV Electric Distribution Networks Including Distributed Generation and ICT Infrastructure," Energies, MDPI, vol. 15(14), pages 1-34, July.

    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. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    2. Lilia Tightiz & Hyosik Yang & Mohammad Jalil Piran, 2020. "A Survey on Enhanced Smart Micro-Grid Management System with Modern Wireless Technology Contribution," Energies, MDPI, vol. 13(9), pages 1-21, May.
    3. Arman Goudarzi & Farzad Ghayoor & Muhammad Waseem & Shah Fahad & Issa Traore, 2022. "A Survey on IoT-Enabled Smart Grids: Emerging, Applications, Challenges, and Outlook," Energies, MDPI, vol. 15(19), pages 1-32, September.
    4. Constantin Aurelian Ionescu & Melinda Timea Fülöp & Dan Ioan Topor & Sorinel Căpușneanu & Teodora Odett Breaz & Sorina Geanina Stănescu & Mihaela Denisa Coman, 2021. "The New Era of Business Digitization through the Implementation of 5G Technology in Romania," Sustainability, MDPI, vol. 13(23), pages 1-23, December.
    5. Zeljko Martinovic & Martin Dadic & Branimir Ivsic & Roman Malaric, 2019. "An Adiabatic Coaxial Line for Microcalorimeter Power Measurements in Wireless Communication for Smart Grid," Energies, MDPI, vol. 12(21), pages 1-18, November.
    6. Alaa Alaerjan, 2023. "Automatic Recognition of Beam Attachment for Massive MIMO System in Densely Distributed Renewable Energy Resources," Sustainability, MDPI, vol. 15(11), pages 1-19, May.
    7. Ibrahim Abaker Targio Hashem & Raja Sher Afgun Usmani & Mubarak S. Almutairi & Ashraf Osman Ibrahim & Abubakar Zakari & Faiz Alotaibi & Saadat Mehmood Alhashmi & Haruna Chiroma, 2023. "Urban Computing for Sustainable Smart Cities: Recent Advances, Taxonomy, and Open Research Challenges," Sustainability, MDPI, vol. 15(5), pages 1-32, February.
    8. Edward Smith & Duane Robinson & Ashish Agalgaonkar, 2021. "Cooperative Control of Microgrids: A Review of Theoretical Frameworks, Applications and Recent Developments," Energies, MDPI, vol. 14(23), pages 1-34, December.
    9. Zubair Khalid & Ghulam Abbas & Muhammad Awais & Thamer Alquthami & Muhammad Babar Rasheed, 2020. "A Novel Load Scheduling Mechanism Using Artificial Neural Network Based Customer Profiles in Smart Grid," Energies, MDPI, vol. 13(5), pages 1-23, February.
    10. Hui, Hongxun & Ding, Yi & Shi, Qingxin & Li, Fangxing & Song, Yonghua & Yan, Jinyue, 2020. "5G network-based Internet of Things for demand response in smart grid: A survey on application potential," Applied Energy, Elsevier, vol. 257(C).
    11. Christos-Minas Mathas & Costas Vassilakis & Nicholas Kolokotronis & Charilaos C. Zarakovitis & Michail-Alexandros Kourtis, 2021. "On the Design of IoT Security: Analysis of Software Vulnerabilities for Smart Grids," Energies, MDPI, vol. 14(10), pages 1-27, May.
    12. Jiayu Cheng & Dongliang Duan & Xiang Cheng & Liuqing Yang & Shuguang Cui, 2021. "Adaptive Control for Energy Exchange with Probabilistic Interval Predictors in Isolated Microgrids," Energies, MDPI, vol. 14(2), pages 1-23, January.
    13. Ali Gohar & Gianfranco Nencioni, 2021. "The Role of 5G Technologies in a Smart City: The Case for Intelligent Transportation System," Sustainability, MDPI, vol. 13(9), pages 1-24, May.

    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:13:y:2020:i:12:p:3245-:d:375172. 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.