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A Review of Methodologies for Managing Energy Flexibility Resources in Buildings

Author

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  • Omid Pedram

    (Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal)

  • Ehsan Asadi

    (Associação para o Desenvolvimento da Aerodinâmica Industrial—ADAI, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal)

  • Behrang Chenari

    (Associação para o Desenvolvimento da Aerodinâmica Industrial—ADAI, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal)

  • Pedro Moura

    (Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal
    Institute of Systems and Robotics, University of Coimbra, 3030-290 Coimbra, Portugal)

  • Manuel Gameiro da Silva

    (Associação para o Desenvolvimento da Aerodinâmica Industrial—ADAI, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal)

Abstract

The integration of renewable energy and flexible energy sources in buildings brings numerous benefits. However, the integration of new technologies has increased the complexity and despite the progress of optimization algorithms and technologies, new research challenges emerge. With the increasing availability of data and advanced modeling tools, stakeholders in the building sector are actively seeking a more comprehensive understanding of the implementation and potential benefits of energy optimization and an extensive up-to-date survey of optimization in the context of buildings and communities is missing in the literature. This study comprehensively reviews over 180 relevant publications on the management and optimization of energy flexibility resources in buildings. The primary objective was to examine and analyze prior research, with emphasis on the used methods, objectives, and scope. The method of content analysis was used to ensure a thorough examination of the existing literature on the subject. It was concluded that multi-objective optimization is crucial to enhance the utilization of flexible resources within individual buildings and communities. Moreover, the study successfully pinpointed key challenges and opportunities for future research, such as the need for accurate data, the complexity of the optimization process, and the potential trade-offs between different objectives.

Suggested Citation

  • Omid Pedram & Ehsan Asadi & Behrang Chenari & Pedro Moura & Manuel Gameiro da Silva, 2023. "A Review of Methodologies for Managing Energy Flexibility Resources in Buildings," Energies, MDPI, vol. 16(17), pages 1-30, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6111-:d:1222286
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    References listed on IDEAS

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    4. Yinan Li & Neng Zhu & Beibei Qin, 2019. "What Affects the Progress and Transformation of New Residential Building Energy Efficiency Promotion in China: Stakeholders’ Perceptions," Energies, MDPI, vol. 12(6), pages 1-41, March.
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    Cited by:

    1. Abdelhamid Zaidi, 2024. "Utilisation of Deep Learning (DL) and Neural Networks (NN) Algorithms for Energy Power Generation: A Social Network and Bibliometric Analysis (2004-2022)," International Journal of Energy Economics and Policy, Econjournals, vol. 14(1), pages 172-183, January.
    2. Danielle Bandeira Mello Delgado & Iderval Costa e Silva Neto & Monica Carvalho, 2025. "Strategies for Multigeneration in Residential Energy Systems: An Optimization Approach," Sustainability, MDPI, vol. 17(3), pages 1-17, January.

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