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Data Distribution Service-Based Interoperability Framework for Smart Grid Testbed Infrastructure

Author

Listed:
  • Tarek A. Youssef

    (Energy Systems Research Laboratory, Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA)

  • Ahmed T. Elsayed

    (Energy Systems Research Laboratory, Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA)

  • Osama A. Mohammed

    (Energy Systems Research Laboratory, Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA)

Abstract

This paper presents the design and implementation of a communication and control infrastructure for smart grid operation. The proposed infrastructure enhances the reliability of the measurements and control network. The advantages of utilizing the data-centric over message-centric communication approach are discussed in the context of smart grid applications. The data distribution service (DDS) is used to implement a data-centric common data bus for the smart grid. This common data bus improves the communication reliability, enabling distributed control and smart load management. These enhancements are achieved by avoiding a single point of failure while enabling peer-to-peer communication and an automatic discovery feature for dynamic participating nodes. The infrastructure and ideas presented in this paper were implemented and tested on the smart grid testbed. A toolbox and application programing interface for the testbed infrastructure are developed in order to facilitate interoperability and remote access to the testbed. This interface allows control, monitoring, and performing of experiments remotely. Furthermore, it could be used to integrate multidisciplinary testbeds to study complex cyber-physical systems (CPS).

Suggested Citation

  • Tarek A. Youssef & Ahmed T. Elsayed & Osama A. Mohammed, 2016. "Data Distribution Service-Based Interoperability Framework for Smart Grid Testbed Infrastructure," Energies, MDPI, vol. 9(3), pages 1-22, March.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:3:p:150-:d:64881
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    References listed on IDEAS

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    1. Luca Ardito & Giuseppe Procaccianti & Giuseppe Menga & Maurizio Morisio, 2013. "Smart Grid Technologies in Europe: An Overview," Energies, MDPI, vol. 6(1), pages 1-31, January.
    2. Mohamed A. Ahmed & Yong Cheol Kang & Young-Chon Kim, 2015. "Communication Network Architectures for Smart-House with Renewable Energy Resources," Energies, MDPI, vol. 8(8), pages 1-20, August.
    3. Rubén De Diego & José-Fernán Martínez & Jesús Rodríguez-Molina & Alexandra Cuerva, 2014. "A Semantic Middleware Architecture Focused on Data and Heterogeneity Management within the Smart Grid," Energies, MDPI, vol. 7(9), pages 1-42, September.
    4. José-Fernán Martínez & Jesús Rodríguez-Molina & Pedro Castillejo & Rubén De Diego, 2013. "Middleware Architectures for the Smart Grid: Survey and Challenges in the Foreseeable Future," Energies, MDPI, vol. 6(7), pages 1-29, July.
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    Cited by:

    1. Silvia Marzal & Raul González-Medina & Robert Salas-Puente & Emilio Figueres & Gabriel Garcerá, 2017. "A Novel Locality Algorithm and Peer-to-Peer Communication Infrastructure for Optimizing Network Performance in Smart Microgrids," Energies, MDPI, vol. 10(9), pages 1-25, August.
    2. Lilia Tightiz & Hyosik Yang, 2020. "A Comprehensive Review on IoT Protocols’ Features in Smart Grid Communication," Energies, MDPI, vol. 13(11), pages 1-24, June.
    3. Ridlo Sayyidina Auliya & Chia-Ching Chen & Po-Ru Lin & Deron Liang & Wei-Jen Wang, 2023. "Optimization of message delivery reliability and throughput in a DDS-based system with per-publisher sending rate adjustment," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 84(2), pages 235-250, October.
    4. Fatima Zahra Harmouch & Ahmed F. Ebrahim & Mohammad Mahmoudian Esfahani & Nissrine Krami & Nabil Hmina & Osama A. Mohammed, 2019. "An Optimal Energy Management System for Real-Time Operation of Multiagent-Based Microgrids Using a T-Cell Algorithm," Energies, MDPI, vol. 12(15), pages 1-23, August.

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