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Experimental Validation of Peer-to-Peer Distributed Voltage Control System

Author

Listed:
  • Hamada Almasalma

    (Departement Elektrotechniek, KU Leuven, Kasteelpark Arenberg 10, 3001 Leuven, Belgium
    EnergyVille Research Center, Thor Park 8310, 3600 Genk, Belgium)

  • Sander Claeys

    (Departement Elektrotechniek, KU Leuven, Kasteelpark Arenberg 10, 3001 Leuven, Belgium
    EnergyVille Research Center, Thor Park 8310, 3600 Genk, Belgium)

  • Konstantin Mikhaylov

    (Centre for Wireless Communications (CWC), University of Oulu, 90014 Oulu, Finland)

  • Jussi Haapola

    (Centre for Wireless Communications (CWC), University of Oulu, 90014 Oulu, Finland)

  • Ari Pouttu

    (Centre for Wireless Communications (CWC), University of Oulu, 90014 Oulu, Finland)

  • Geert Deconinck

    (Departement Elektrotechniek, KU Leuven, Kasteelpark Arenberg 10, 3001 Leuven, Belgium
    EnergyVille Research Center, Thor Park 8310, 3600 Genk, Belgium)

Abstract

This paper presents experimental validation of a distributed optimization-based voltage control system. The dual-decomposition method is used in this paper to solve the voltage optimization problem in a fully distributed way. Device-to-device communication is implemented to enable peer-to-peer data exchange between agents of the proposed voltage control system. The paper presents the design, development and hardware setup of a laboratory-based testbed used to validate the performance of the proposed dual-decomposition-based peer-to-peer voltage control. The architecture of the setup consists of four layers: microgrid, control, communication, and monitoring. The key question motivating this research was whether distributed voltage control systems are a technically effective alternative to centralized ones. The results discussed in this paper show that distributed voltage control systems can indeed provide satisfactory regulation of the voltage profiles.

Suggested Citation

  • Hamada Almasalma & Sander Claeys & Konstantin Mikhaylov & Jussi Haapola & Ari Pouttu & Geert Deconinck, 2018. "Experimental Validation of Peer-to-Peer Distributed Voltage Control System," Energies, MDPI, vol. 11(5), pages 1-22, May.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:5:p:1304-:d:148042
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    References listed on IDEAS

    as
    1. Cagnano, A. & De Tuglie, E., 2016. "A decentralized voltage controller involving PV generators based on Lyapunov theory," Renewable Energy, Elsevier, vol. 86(C), pages 664-674.
    2. Nijhuis, M. & Gibescu, M. & Cobben, J.F.G., 2015. "Assessment of the impacts of the renewable energy and ICT driven energy transition on distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1003-1014.
    3. Marzband, Mousa & Azarinejadian, Fatemeh & Savaghebi, Mehdi & Pouresmaeil, Edris & Guerrero, Josep M. & Lightbody, Gordon, 2018. "Smart transactive energy framework in grid-connected multiple home microgrids under independent and coalition operations," Renewable Energy, Elsevier, vol. 126(C), pages 95-106.
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    Cited by:

    1. Dudjak, Viktorija & Neves, Diana & Alskaif, Tarek & Khadem, Shafi & Pena-Bello, Alejandro & Saggese, Pietro & Bowler, Benjamin & Andoni, Merlinda & Bertolini, Marina & Zhou, Yue & Lormeteau, Blanche &, 2021. "Impact of local energy markets integration in power systems layer: A comprehensive review," Applied Energy, Elsevier, vol. 301(C).
    2. Almasalma, Hamada & Claeys, Sander & Deconinck, Geert, 2019. "Peer-to-peer-based integrated grid voltage support function for smart photovoltaic inverters," Applied Energy, Elsevier, vol. 239(C), pages 1037-1048.
    3. Thomas I. Strasser & Sebastian Rohjans & Graeme M. Burt, 2019. "Methods and Concepts for Designing and Validating Smart Grid Systems," Energies, MDPI, vol. 12(10), pages 1-5, May.
    4. Jean-François Toubeau & Bashir Bakhshideh Zad & Martin Hupez & Zacharie De Grève & François Vallée, 2020. "Deep Reinforcement Learning-Based Voltage Control to Deal with Model Uncertainties in Distribution Networks," Energies, MDPI, vol. 13(15), pages 1-15, August.
    5. Daiva Stanelytė & Virginijus Radziukynas, 2022. "Analysis of Voltage and Reactive Power Algorithms in Low Voltage Networks," Energies, MDPI, vol. 15(5), pages 1-26, March.
    6. Francisco de Paula García-López & Manuel Barragán-Villarejo & Alejandro Marano-Marcolini & José María Maza-Ortega & José Luis Martínez-Ramos, 2018. "Experimental Assessment of a Centralised Controller for High-RES Active Distribution Networks," Energies, MDPI, vol. 11(12), pages 1-16, December.
    7. Olamide Jogunola & Bamidele Adebisi & Kelvin Anoh & Augustine Ikpehai & Mohammad Hammoudeh & Georgina Harris & Haris Gacanin, 2018. "Distributed Adaptive Primal Algorithm for P2P-ETS over Unreliable Communication Links," Energies, MDPI, vol. 11(9), pages 1-16, September.
    8. Bashir Bakhshideh Zad & Jean-François Toubeau & François Vallée, 2021. "Chance-Constrained Based Voltage Control Framework to Deal with Model Uncertainties in MV Distribution Systems," Energies, MDPI, vol. 14(16), pages 1-16, August.

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