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Sizing with Technical Indicators of Microgrids with Battery Energy Storage Systems: A Systematic Review

Author

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  • Andrea Vasconcelos

    (Edson Mororo Moura Institute of Technology, Recife 51020-280, Brazil
    Department of Computer Engineering, Polytechnic College, University of Pernambuco, Recife 50720-001, Brazil)

  • Amanda Monteiro

    (Edson Mororo Moura Institute of Technology, Recife 51020-280, Brazil)

  • Tatiane Costa

    (Edson Mororo Moura Institute of Technology, Recife 51020-280, Brazil)

  • Ana Clara Rode

    (AES Brasil, R&D and Innovation, Sao Paulo 04578-000, Brazil)

  • Manoel H. N. Marinho

    (Edson Mororo Moura Institute of Technology, Recife 51020-280, Brazil
    Department of Computer Engineering, Polytechnic College, University of Pernambuco, Recife 50720-001, Brazil)

  • Roberto Dias Filho

    (Edson Mororo Moura Institute of Technology, Recife 51020-280, Brazil
    Department of Computer Engineering, Polytechnic College, University of Pernambuco, Recife 50720-001, Brazil)

  • Alexandre M. A. Maciel

    (Department of Computer Engineering, Polytechnic College, University of Pernambuco, Recife 50720-001, Brazil)

Abstract

Worldwide, governmental organizations are restructuring energy policies, making them cleaner, encouraging transformation and energy transition by integrating renewable sources, engaging in environmental preservation, and, notably, meeting the growing demand for sustainable energy models, such as solar and wind energy. In the electricity sector, reducing carbon emissions is crucial to facilitating the integration of microgrids (MGs) with renewable sources and Battery Energy Storage Systems (BESSs). This work constitutes a systematic review that thoroughly analyzes the sizing of MGs with BESSs. The unpredictability and variability of renewable sources justify the complexity of this analysis and the loads connected to the system. Additionally, the sizing of a BESS depends primarily on the application, battery technology, and the system’s energy demand. This review mapped and identified existing computational and optimization methodologies for structured sizing in technical indicators of an MG with a BESS based on articles published between 2017 and 2021. A protocol was defined in which articles were filtered in multiple stages, undergoing strategic refinements to arrive at the final articles to address the Research Questions (RQs). The final number of articles was 44, and within these, technical indicators related to the RQs were addressed, covering the most relevant works and comparing them technically, including how each explains the objective and result of their work. The rejected articles did not meet the criteria established by the defined protocol, such as exclusion criteria, quality criteria, and RQs. In conclusion, studies employing the integration of machine learning coupled with optimization techniques exhibit a significant contribution to results, as historical data can aid machine learning for data prediction.

Suggested Citation

  • Andrea Vasconcelos & Amanda Monteiro & Tatiane Costa & Ana Clara Rode & Manoel H. N. Marinho & Roberto Dias Filho & Alexandre M. A. Maciel, 2023. "Sizing with Technical Indicators of Microgrids with Battery Energy Storage Systems: A Systematic Review," Energies, MDPI, vol. 16(24), pages 1-26, December.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:8095-:d:1301308
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    References listed on IDEAS

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    1. Tang, Rui & Yildiz, Baran & Leong, Philip H.W. & Vassallo, Anthony & Dore, Jonathon, 2019. "Residential battery sizing model using net meter energy data clustering," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    2. Schopfer, S. & Tiefenbeck, V. & Staake, T., 2018. "Economic assessment of photovoltaic battery systems based on household load profiles," Applied Energy, Elsevier, vol. 223(C), pages 229-248.
    3. Soheil Mohseni & Alan C. Brent & Daniel Burmester, 2021. "Off-Grid Multi-Carrier Microgrid Design Optimisation: The Case of Rakiura–Stewart Island, Aotearoa–New Zealand," Energies, MDPI, vol. 14(20), pages 1-28, October.
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    1. Djalma M. Falcão & Sun Tao & Glauco N. Taranto & Thiago J. Masseran A. Parreiras & Murilo E. C. Bento & Dany H. Huanca & Hugo Muzitano & Paulo Esmeraldo & Pedro Lima & Lillian Monteath & Roberto Brand, 2024. "Case Studies of Battery Energy Storage System Applications in the Brazilian Transmission System," Energies, MDPI, vol. 17(22), pages 1-16, November.

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