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Exploiting OLTC and BESS Operation Coordinated with Active Network Management in LV Networks

Author

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  • Konstantinos Kotsalos

    (Faculty of Engineering (FEUP), University of Porto, 4200-465 Porto, Portugal
    Current address: Rua Barata Feyo 125 R/C 0A1, 4250-075 Porto, Portugal.)

  • Ismael Miranda

    (Efacec, Division of Storage, 4471-907 Porto, Portugal)

  • Jose Luis Dominguez-Garcia

    (Electrical Power Systems Area, Catalonia Institute for Energy Research (IREC), 08930 Barcelona, Spain)

  • Helder Leite

    (Faculty of Engineering (FEUP), University of Porto, 4200-465 Porto, Portugal)

  • Nuno Silva

    (Efacec, Division of T&I, 4466-952 Porto, Portugal)

  • Nikos Hatziargyriou

    (School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), 15780 Zografou, Greece)

Abstract

The large number of small scale Distributed Energy Resources (DER) such as Electric Vehicles (EVs), rooftop photovoltaic installations and Battery Energy Storage Systems (BESS), installed along distribution networks, poses several challenges related to power quality, efficiency, and reliability. Concurrently, the connection of DER may provide substantial flexibility to the operation of distribution grids and market players such as aggregators. This paper proposes an optimization framework for the energy management and scheduling of operation for Low Voltage (LV) networks assuring both admissible voltage magnitudes and minimized line congestion and voltage unbalances. The proposed tool allows the utilization and coordination of On-Load Tap Changer (OLTC) distribution transformers, BESS, and flexibilities provided by DER. The methodology is framed with a multi-objective three phase unbalanced multi-period AC Optimal Power Flow (MACOPF) solved as a nonlinear optimization problem. The performance of the resulting control scheme is validated on a LV distribution network through multiple case scenarios with high microgeneration and EV integration. The usefulness of the proposed scheme is additionally demonstrated by deriving the most efficient placement and sizing BESS solution based on yearly synthetic load and generation data-set. A techno-economical analysis is also conducted to identify optimal coordination among assets and DER for several objectives.

Suggested Citation

  • Konstantinos Kotsalos & Ismael Miranda & Jose Luis Dominguez-Garcia & Helder Leite & Nuno Silva & Nikos Hatziargyriou, 2020. "Exploiting OLTC and BESS Operation Coordinated with Active Network Management in LV Networks," Sustainability, MDPI, vol. 12(8), pages 1-25, April.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3332-:d:347811
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    References listed on IDEAS

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    1. Razavi, Seyed-Ehsan & Rahimi, Ehsan & Javadi, Mohammad Sadegh & Nezhad, Ali Esmaeel & Lotfi, Mohamed & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Impact of distributed generation on protection and voltage regulation of distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 157-167.
    2. García-Villalobos, J. & Zamora, I. & Knezović, K. & Marinelli, M., 2016. "Multi-objective optimization control of plug-in electric vehicles in low voltage distribution networks," Applied Energy, Elsevier, vol. 180(C), pages 155-168.
    3. Konstantinos Kotsalos & Ismael Miranda & Nuno Silva & Helder Leite, 2019. "A Horizon Optimization Control Framework for the Coordinated Operation of Multiple Distributed Energy Resources in Low Voltage Distribution Networks," Energies, MDPI, vol. 12(6), pages 1-27, March.
    4. Samadi, Afshin & Shayesteh, Ebrahim & Eriksson, Robert & Rawn, Barry & Söder, Lennart, 2014. "Multi-objective coordinated droop-based voltage regulation in distribution grids with PV systems," Renewable Energy, Elsevier, vol. 71(C), pages 315-323.
    5. Pinto, Rui & Bessa, Ricardo J. & Matos, Manuel A., 2017. "Multi-period flexibility forecast for low voltage prosumers," Energy, Elsevier, vol. 141(C), pages 2251-2263.
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    Cited by:

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