IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i12p3098-d371935.html
   My bibliography  Save this article

Investigation of Deterministic, Statistical and Parametric NB-PLC Channel Modeling Techniques for Advanced Metering Infrastructure

Author

Listed:
  • Bilal Masood

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • M. Arif Khan

    (School of Computing and Mathematics, Charles Sturt University, Bathurst, NSW 2678, Australia)

  • Sobia Baig

    (Electrical and Computer Engineering Department, COMSATS University Isb- Lahore Campus, Punjab 54000, Pakistan)

  • Guobing Song

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Ateeq Ur Rehman

    (College of Internet of Things Engineering, Hohai University, Changzhou 213022, China
    Department of Electrical Engineering, Government College University, Lahore 54000, Pakistan)

  • Saif Ur Rehman

    (Department of Electrical Engineering, The Superior College, Lahore 54000, Pakistan)

  • Rao M. Asif

    (Department of Electrical Engineering, The Superior College, Lahore 54000, Pakistan)

  • Muhammad Babar Rasheed

    (Department of Electronics and Electrical Systems, The University of Lahore, Lahore, Punjab 54000, Pakistan)

Abstract

This paper is focused on the channel modeling techniques for implementation of narrowband power line communication (NB-PLC) over medium voltage (MV) network for the purpose of advanced metering infrastructure (AMI). Three different types of models, based on deterministic method, statistical method, and network parameters based method are investigated in detail. Transmission line (TL) theory model is used to express the MV network as a two-port network to examine characteristics of sending and receiving NB-PLC signals. Multipath signal propagation model is used to incorporate the effect of multipath signals to determine the NB-PLC transfer function. A Simulink model is proposed which considers the values of MV network to examine the characteristics of NB-PLC signals. Frequency selectivity is also introduced in the impedances to compare variations and characteristics with constant impedances based MV network. A state-of-the-art mechanism for the modeling of capacitive coupling device, and impedances of low voltage (LV) and MV networks is developed. Moreover, a comparative analysis of TL theory and multipath signal propagation models with the proposed Simulink model is presented to validate the performance and accuracy of proposed model. This research work will pave the way to improve the efficiency of next-generation NB-PLC technologies.

Suggested Citation

  • Bilal Masood & M. Arif Khan & Sobia Baig & Guobing Song & Ateeq Ur Rehman & Saif Ur Rehman & Rao M. Asif & Muhammad Babar Rasheed, 2020. "Investigation of Deterministic, Statistical and Parametric NB-PLC Channel Modeling Techniques for Advanced Metering Infrastructure," Energies, MDPI, vol. 13(12), pages 1-20, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3098-:d:371935
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/12/3098/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/12/3098/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Masood, Bilal & Baig, Sobia, 2016. "Standardization and deployment scenario of next generation NB-PLC technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1033-1047.
    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. Herodotos Herodotou, 2021. "Introduction to the Special Issue on Data-Intensive Computing in Smart Microgrids," Energies, MDPI, vol. 14(9), pages 1-3, May.
    2. Chandan Swaroop Meena & Ashwani Kumar & Siddharth Jain & Ateeq Ur Rehman & Sachin Mishra & Naveen Kumar Sharma & Mohit Bajaj & Muhammad Shafiq & Elsayed Tag Eldin, 2022. "Innovation in Green Building Sector for Sustainable Future," Energies, MDPI, vol. 15(18), pages 1-16, September.
    3. David S. Ching & Cosmin Safta & Thomas A. Reichardt, 2021. "Sensitivity-Informed Bayesian Inference for Home PLC Network Models with Unknown Parameters," Energies, MDPI, vol. 14(9), pages 1-21, April.
    4. Rizwan Tariq & Ibrahim Alhamrouni & Ateeq Ur Rehman & Elsayed Tag Eldin & Muhammad Shafiq & Nivin A. Ghamry & Habib Hamam, 2022. "An Optimized Solution for Fault Detection and Location in Underground Cables Based on Traveling Waves," Energies, MDPI, vol. 15(17), pages 1-19, September.
    5. Adnan Yousaf & Rao Muhammad Asif & Mustafa Shakir & Ateeq Ur Rehman & Fawaz Alassery & Habib Hamam & Omar Cheikhrouhou, 2021. "A Novel Machine Learning-Based Price Forecasting for Energy Management Systems," Sustainability, MDPI, vol. 13(22), pages 1-26, November.
    6. Adnan Yousaf & Rao Muhammad Asif & Mustafa Shakir & Ateeq Ur Rehman & Mohmmed S. Adrees, 2021. "An Improved Residential Electricity Load Forecasting Using a Machine-Learning-Based Feature Selection Approach and a Proposed Integration Strategy," Sustainability, MDPI, vol. 13(11), pages 1-20, May.
    7. Hina Maqbool & Adnan Yousaf & Rao Muhammad Asif & Ateeq Ur Rehman & Elsayed Tag Eldin & Muhammad Shafiq & Habib Hamam, 2022. "An Optimized Fuzzy Based Control Solution for Frequency Oscillation Reduction in Electric Grids," Energies, MDPI, vol. 15(19), pages 1-21, September.
    8. Bilal Masood & Song Guobing & Jamel Nebhen & Ateeq Ur Rehman & Muhammad Naveed Iqbal & Iftikhar Rasheed & Mohit Bajaj & Muhammad Shafiq & Habib Hamam, 2022. "Investigation and Field Measurements for Demand Side Management Control Technique of Smart Air Conditioners located at Residential, Commercial, and Industrial Sites," Energies, MDPI, vol. 15(7), pages 1-23, March.

    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. Giovanni Artale & Antonio Cataliotti & Valentina Cosentino & Dario Di Cara & Riccardo Fiorelli & Salvatore Guaiana & Nicola Panzavecchia & Giovanni Tinè, 2019. "A New Coupling Solution for G3-PLC Employment in MV Smart Grids," Energies, MDPI, vol. 12(13), pages 1-23, June.
    2. Bilal Masood & Song Guobing & Jamel Nebhen & Ateeq Ur Rehman & Muhammad Naveed Iqbal & Iftikhar Rasheed & Mohit Bajaj & Muhammad Shafiq & Habib Hamam, 2022. "Investigation and Field Measurements for Demand Side Management Control Technique of Smart Air Conditioners located at Residential, Commercial, and Industrial Sites," Energies, MDPI, vol. 15(7), pages 1-23, March.
    3. Ying Cui & Xiaosheng Liu & Jian Cao & Dianguo Xu, 2018. "Network Performance Optimization for Low-Voltage Power Line Communications," Energies, MDPI, vol. 11(5), pages 1-25, May.

    More about this item

    Keywords

    AMI; TL; SG; NB-PLC;
    All these keywords.

    Statistics

    Access and download statistics

    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:3098-:d:371935. 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.