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Hierarchical Two-Layer Distributed Control Architecture for Voltage Regulation in Multiple Microgrids in the Presence of Time-Varying Delays

Author

Listed:
  • Amedeo Andreotti

    (Department of Information Technology and Electrical Engineering (DIETI), University of Naples Federico II, 80125 Naples, Italy
    Authors are in alphabetic order.)

  • Bianca Caiazzo

    (Department of Information Technology and Electrical Engineering (DIETI), University of Naples Federico II, 80125 Naples, Italy
    Authors are in alphabetic order.)

  • Alberto Petrillo

    (Department of Information Technology and Electrical Engineering (DIETI), University of Naples Federico II, 80125 Naples, Italy
    Authors are in alphabetic order.)

  • Stefania Santini

    (Department of Information Technology and Electrical Engineering (DIETI), University of Naples Federico II, 80125 Naples, Italy
    Authors are in alphabetic order.)

  • Alfredo Vaccaro

    (Department of Engineering, University of Sannio, 82100 Benevento, Italy
    Authors are in alphabetic order.)

Abstract

The Multiple Microgrids (MMGs) concept has been identified as a promising solution for the management of large-scale power grids in order to maximize the use of widespread renewable energies sources. However, its deployment in realistic operation scenarios is still an open issue due to the presence of non-ideal and unreliable communication systems that allow each component within the power network to share information about its state. Indeed, due to technological constraints, multiple time-varying communication delays consistently appear during data acquisition and the transmission process and their effects must be considered in the control design phase. To this aim, this paper addresses the voltage regulation control problem for MMGs systems in the presence of time-varying communication delays. To solve this problem, we propose a novel hierarchical two-layer distributed control architecture that accounts for the presence of communication latencies in the information exchange. More specifically, the upper control layer aims at guaranteeing a proper and economical reactive power dispatch among MMGs, while the lower control layer aims at ensuring voltage regulation of all electrical buses within each MG to the desired voltage set-point. By leveraging a proper Driver Generator Nodes Selection Algorithm, we first provide the best choice of generator nodes which, considering the upper layer control goal, speeds up the voltage synchronization process of all the buses within each MG to the voltage set-point computed by the upper-control layer. Then, the lower control layer, on the basis of this desired voltage value, drives the reactive power capability of each smart device within each MG and compensates for possible voltage deviations. Simulation analysis is carried out on the realistic case study of an MMGs system consisting of two identical IEEE 14-bus test systems and the numerical results disclose the effectiveness of the proposed control strategy, as well as its robustness with respect to load fluctuations.

Suggested Citation

  • Amedeo Andreotti & Bianca Caiazzo & Alberto Petrillo & Stefania Santini & Alfredo Vaccaro, 2020. "Hierarchical Two-Layer Distributed Control Architecture for Voltage Regulation in Multiple Microgrids in the Presence of Time-Varying Delays," Energies, MDPI, vol. 13(24), pages 1-19, December.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:24:p:6507-:d:459446
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    References listed on IDEAS

    as
    1. Amedeo Andreotti & Alberto Petrillo & Stefania Santini & Alfredo Vaccaro & Domenico Villacci, 2019. "A Decentralized Architecture Based on Cooperative Dynamic Agents for Online Voltage Regulation in Smart Grids," Energies, MDPI, vol. 12(7), pages 1-14, April.
    2. Barra, P.H.A. & Coury, D.V. & Fernandes, R.A.S., 2020. "A survey on adaptive protection of microgrids and distribution systems with distributed generators," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    3. Yuan Fan & Chengxiao Zhang & Cheng Song, 2018. "Sampling-based self-triggered coordination control for multi-agent systems with application to distributed generators," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(15), pages 3048-3062, November.
    4. Ajoulabadi, Ata & Ravadanegh, Sajad Najafi & Behnam Mohammadi-Ivatloo,, 2020. "Flexible scheduling of reconfigurable microgrid-based distribution networks considering demand response program," Energy, Elsevier, vol. 196(C).
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    Cited by:

    1. Lucas V. Bellinaso & Edivan L. Carvalho & Rafael Cardoso & Leandro Michels, 2021. "Price-Response Matrices Design Methodology for Electrical Energy Management Systems Based on DC Bus Signalling," Energies, MDPI, vol. 14(6), pages 1-19, March.
    2. Villanueva-Rosario, Junior Alexis & Santos-García, Félix & Aybar-Mejía, Miguel Euclides & Mendoza-Araya, Patricio & Molina-García, Angel, 2022. "Coordinated ancillary services, market participation and communication of multi-microgrids: A review," Applied Energy, Elsevier, vol. 308(C).

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