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Optimal Control of Multiple Microgrids and Buildings by an Aggregator

Author

Listed:
  • Giulio Ferro

    (DIBRIS, University of Genoa, via Opera Pia 13, 16145 Genova, Italy)

  • Riccardo Minciardi

    (DIBRIS, University of Genoa, via Opera Pia 13, 16145 Genova, Italy)

  • Luca Parodi

    (DIBRIS, University of Genoa, via Opera Pia 13, 16145 Genova, Italy)

  • Michela Robba

    (DIBRIS, University of Genoa, via Opera Pia 13, 16145 Genova, Italy)

  • Mansueto Rossi

    (DITEN, University of Genoa, via A. Magliotto 2, 17100 Savona, Italy)

Abstract

The electrical grid has been changing in the last decade due to the presence of renewables, distributed generation, storage systems, microgrids, and electric vehicles. The introduction of new legislation and actors in the smart grid’s system opens new challenges for the activities of companies, and for the development of new energy management systems, models, and methods. A new optimization-based bi-level architecture is proposed for an aggregator of consumers in the balancing market, in which incentives for local users (i.e., microgrids, buildings) are considered, as well as flexibility and a fair assignment in reducing the overall load. At the lower level, consumers try to follow the aggregator’s reference values and perform demand response programs to contain their costs and satisfy demands. The approach is applied to a real case study.

Suggested Citation

  • Giulio Ferro & Riccardo Minciardi & Luca Parodi & Michela Robba & Mansueto Rossi, 2020. "Optimal Control of Multiple Microgrids and Buildings by an Aggregator," Energies, MDPI, vol. 13(5), pages 1-23, February.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1058-:d:325881
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    References listed on IDEAS

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    1. Fontenot, Hannah & Dong, Bing, 2019. "Modeling and control of building-integrated microgrids for optimal energy management – A review," Applied Energy, Elsevier, vol. 254(C).
    2. Aghajani, G.R. & Shayanfar, H.A. & Shayeghi, H., 2017. "Demand side management in a smart micro-grid in the presence of renewable generation and demand response," Energy, Elsevier, vol. 126(C), pages 622-637.
    3. Carreiro, Andreia M. & Jorge, Humberto M. & Antunes, Carlos Henggeler, 2017. "Energy management systems aggregators: A literature survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1160-1172.
    4. Feijoo, Felipe & Das, Tapas K., 2015. "Emissions control via carbon policies and microgrid generation: A bilevel model and Pareto analysis," Energy, Elsevier, vol. 90(P2), pages 1545-1555.
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    Cited by:

    1. José Luis Ruiz Duarte & Neng Fan, 2022. "Operation of a Power Grid with Embedded Networked Microgrids and Onsite Renewable Technologies," Energies, MDPI, vol. 15(7), pages 1-24, March.
    2. Giulio Ferro & Michela Robba & Roberto Sacile, 2020. "A Model Predictive Control Strategy for Distribution Grids: Voltage and Frequency Regulation for Islanded Mode Operation," Energies, MDPI, vol. 13(10), pages 1-27, May.
    3. Backe, Stian & Zwickl-Bernhard, Sebastian & Schwabeneder, Daniel & Auer, Hans & Korpås, Magnus & Tomasgard, Asgeir, 2022. "Impact of energy communities on the European electricity and heating system decarbonization pathway: Comparing local and global flexibility responses," Applied Energy, Elsevier, vol. 323(C).
    4. Fernando J. Lanas & Francisco J. Martínez-Conde & Diego Alvarado & Rodrigo Moreno & Patricio Mendoza-Araya & Guillermo Jiménez-Estévez, 2020. "Non-Strategic Capacity Withholding from Distributed Energy Storage within Microgrids Providing Energy and Reserve Services," Energies, MDPI, vol. 13(19), pages 1-14, October.
    5. Lonergan, Katherine Emma & Suter, Nicolas & Sansavini, Giovanni, 2023. "Energy systems modelling for just transitions," Energy Policy, Elsevier, vol. 183(C).

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