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Photovoltaic Power Converter Management in Unbalanced Low Voltage Networks with Ancillary Services Support

Author

Listed:
  • Fermín Barrero-González

    (School of Industrial Engineering, University of Extremadura, 06006 Badajoz, Spain)

  • Victor Fernão Pires

    (INESC-ID and Setúbal School of Technology, Polytechnic Institute of Setúbal, 2910-761 Setúbal, Portugal)

  • José L. Sousa

    (INESC Coimbra and Setúbal School of Technology, Polytechnic Institute of Setúbal, 2910-761 Setúbal, Portugal)

  • João F. Martins

    (Faculty of Sciences and Technology, Nova University of Lisbon, 2829-516 Caparica, Portugal)

  • María Isabel Milanés-Montero

    (School of Industrial Engineering, University of Extremadura, 06006 Badajoz, Spain)

  • Eva González-Romera

    (School of Industrial Engineering, University of Extremadura, 06006 Badajoz, Spain)

  • Enrique Romero-Cadaval

    (School of Industrial Engineering, University of Extremadura, 06006 Badajoz, Spain)

Abstract

The proliferation of residential photovoltaic (PV) prosumers leads to detrimental impacts on the low-voltage (LV) distribution network operation such as reverse power flow, voltage fluctuations and voltage imbalances. This is due to the fact that the strategies for the PV inverters are usually designed to obtain the maximum energy from the panels. The most recent approach to these issues involves new inverter-based solutions. This paper proposes a novel comprehensive control strategy for the power electronic converters associated with PV installations to improve the operational performance of a four-wire LV distribution network. The objectives are to try to balance the currents demanded by consumers and to compensate the reactive power demanded by them at the expense of the remaining converters’ capacity. The strategy is implemented in each consumer installation, constituting a decentralized or distributed control and allowing its practical implementation based on local measurements. The algorithms were tested, in a yearly simulation horizon, on a typical Portuguese LV network to verify the impact of the high integration of the renewable energy sources in the network and the effectiveness and applicability of the proposed approach.

Suggested Citation

  • Fermín Barrero-González & Victor Fernão Pires & José L. Sousa & João F. Martins & María Isabel Milanés-Montero & Eva González-Romera & Enrique Romero-Cadaval, 2019. "Photovoltaic Power Converter Management in Unbalanced Low Voltage Networks with Ancillary Services Support," Energies, MDPI, vol. 12(6), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:6:p:972-:d:213471
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    References listed on IDEAS

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    1. Jin, Peng & Li, Yang & Li, Guoqing & Chen, Zhe & Zhai, Xiaojuan, 2017. "Optimized hierarchical power oscillations control for distributed generation under unbalanced conditions," Applied Energy, Elsevier, vol. 194(C), pages 343-352.
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    3. Maria-Isabel Milanes-Montero & Fermin Barrero-Gonzalez & Jaime Pando-Acedo & Eva Gonzalez-Romera & Enrique Romero-Cadaval & Antonio Moreno-Munoz, 2017. "Active, Reactive and Harmonic Control for Distributed Energy Micro-Storage Systems in Smart Communities Homes," Energies, MDPI, vol. 10(4), pages 1-11, April.
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    Cited by:

    1. Cícero Augusto de Souza & Diego Jose da Silva & Priscila Rossoni & Edmarcio Antonio Belati & Ademir Pelizari & Jesús M. López-Lezama & Nicolás Muñoz-Galeano, 2023. "Multi-Period Optimal Power Flow with Photovoltaic Generation Considering Optimized Power Factor Control," Sustainability, MDPI, vol. 15(19), pages 1-20, September.
    2. Saša Vlahinić & Dubravko Franković & Vitomir Komen & Anamarija Antonić, 2019. "Reactive Power Compensation with PV Inverters for System Loss Reduction," Energies, MDPI, vol. 12(21), pages 1-17, October.
    3. Mohamed Derbeli & Oscar Barambones & Jose Antonio Ramos-Hernanz & Lassaad Sbita, 2019. "Real-Time Implementation of a Super Twisting Algorithm for PEM Fuel Cell Power System," Energies, MDPI, vol. 12(9), pages 1-20, April.
    4. Marco Badami & Gabriele Fambri & Salvatore Mancò & Mariapia Martino & Ioannis G. Damousis & Dimitrios Agtzidis & Dimitrios Tzovaras, 2019. "A Decision Support System Tool to Manage the Flexibility in Renewable Energy-Based Power Systems," Energies, MDPI, vol. 13(1), pages 1-16, December.
    5. Bartłomiej Mroczek & Paweł Pijarski, 2022. "Machine Learning in Operating of Low Voltage Future Grid," Energies, MDPI, vol. 15(15), pages 1-30, July.
    6. Bogdan-Constantin Neagu & Ovidiu Ivanov & Gheorghe Grigoras & Mihai Gavrilas, 2020. "A New Vision on the Prosumers Energy Surplus Trading Considering Smart Peer-to-Peer Contracts," Mathematics, MDPI, vol. 8(2), pages 1-27, February.

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