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Smart Meter Traffic in a Real LV Distribution Network

Author

Listed:
  • Nikoleta Andreadou

    (Energy Security, Distribution and Markets Unit, Energy, Transport and Climate Directorate, Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy)

  • Evangelos Kotsakis

    (Energy Security, Distribution and Markets Unit, Energy, Transport and Climate Directorate, Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy)

  • Marcelo Masera

    (Energy Security, Distribution and Markets Unit, Energy, Transport and Climate Directorate, Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy)

Abstract

The modernization of the distribution grid requires a huge amount of data to be transmitted and handled by the network. The deployment of Advanced Metering Infrastructure systems results in an increased traffic generated by smart meters. In this work, we examine the smart meter traffic that needs to be accommodated by a real distribution system. Parameters such as the message size and the message transmission frequency are examined and their effect on traffic is showed. Limitations of the system are presented, such as the buffer capacity needs and the maximum message size that can be communicated. For this scope, we have used the parameters of a real distribution network, based on a survey at which the European Distribution System Operators (DSOs) have participated. For the smart meter traffic, we have used two popular specifications, namely the G3-PLC–“G3 Power Line communication” and PRIME–acronym for “PoweRline Intelligent Metering Evolution”, to simulate the characteristics of a system that is widely used in practice. The results can be an insight for further development of the Information and Communication Technology (ICT) systems that control and monitor the Low Voltage (LV) distribution grid. The paper presents an analysis towards identifying the needs of distribution networks with respect to telecommunication data as well as the main parameters that can affect the Inverse Fast Fourier Transform (IFFT) system performance. Identifying such parameters is consequently beneficial to designing more efficient ICT systems for Advanced Metering Infrastructure.

Suggested Citation

  • Nikoleta Andreadou & Evangelos Kotsakis & Marcelo Masera, 2018. "Smart Meter Traffic in a Real LV Distribution Network," Energies, MDPI, vol. 11(5), pages 1-27, May.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:5:p:1156-:d:144766
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    References listed on IDEAS

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    1. Nikoleta Andreadou & Miguel Olariaga Guardiola & Gianluca Fulli, 2016. "Telecommunication Technologies for Smart Grid Projects with Focus on Smart Metering Applications," Energies, MDPI, vol. 9(5), pages 1-35, May.
    2. Fateh Nassim Melzi & Allou Same & Mohamed Haykel Zayani & Latifa Oukhellou, 2017. "A Dedicated Mixture Model for Clustering Smart Meter Data: Identification and Analysis of Electricity Consumption Behaviors," Energies, MDPI, vol. 10(10), pages 1-21, September.
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    Cited by:

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    3. 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.
    4. Chaminda Bandara, W.G. & Godaliyadda, G.M.R.I. & Ekanayake, M.P.B. & Ekanayake, J.B., 2020. "Coordinated photovoltaic re-phasing: A novel method to maximize renewable energy integration in low voltage networks by mitigating network unbalances," Applied Energy, Elsevier, vol. 280(C).
    5. Yueqiang Xu & Petri Ahokangas & Jean-Nicolas Louis & Eva Pongrácz, 2019. "Electricity Market Empowered by Artificial Intelligence: A Platform Approach," Energies, MDPI, vol. 12(21), pages 1-21, October.
    6. Roberto Massi Oliveira & Luiz Filipe Menezes Vieira & Marcos Augusto Menezes Vieira & Alex Borges Vieira, 2021. "A dynamic network coding MAC protocol for power line communication," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 77(2), pages 359-375, June.

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