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A Review of Key Performance Indicators for Building Flexibility Quantification to Support the Clean Energy Transition

Author

Listed:
  • Girolama Airò Farulla

    (Dipartimento di Ingegneria, Università degli Studi di Palermo, 90128 Palermo, Italy)

  • Giovanni Tumminia

    (Istituto di Tecnologie Avanzate per l’Energia “Nicola Giordano”, Consiglio Nazionale delle Ricerche, 98126 Messina, Italy)

  • Francesco Sergi

    (Istituto di Tecnologie Avanzate per l’Energia “Nicola Giordano”, Consiglio Nazionale delle Ricerche, 98126 Messina, Italy)

  • Davide Aloisio

    (Istituto di Tecnologie Avanzate per l’Energia “Nicola Giordano”, Consiglio Nazionale delle Ricerche, 98126 Messina, Italy)

  • Maurizio Cellura

    (Dipartimento di Ingegneria, Università degli Studi di Palermo, 90128 Palermo, Italy
    Istituto di Tecnologie Avanzate per l’Energia “Nicola Giordano”, Consiglio Nazionale delle Ricerche, 98126 Messina, Italy)

  • Vincenzo Antonucci

    (Istituto di Tecnologie Avanzate per l’Energia “Nicola Giordano”, Consiglio Nazionale delle Ricerche, 98126 Messina, Italy)

  • Marco Ferraro

    (Istituto di Tecnologie Avanzate per l’Energia “Nicola Giordano”, Consiglio Nazionale delle Ricerche, 98126 Messina, Italy)

Abstract

The transition to a sustainable society and a carbon-neutral economy by 2050 requires extensive deployment of renewable energy sources that, due to the aleatority and non-programmability of most of them, may seriously affect the stability of existing power grids. In this context, buildings are increasingly being seen as a potential source of energy flexibility for the power grid. In literature, key performance indicators, allowing different aspects of the load management, are used to investigate buildings’ energy flexibility. The paper reviews existing indicators developed in the context of theoretical, experimental and numerical studies on flexible buildings, outlining the current status and the potential future perspective. Moreover, the paper briefly reviews the range of grid services that flexible buildings can provide to support the reliability of the electric power system which is potentially challenged by the increasing interconnection of distributed variable renewable generation.

Suggested Citation

  • Girolama Airò Farulla & Giovanni Tumminia & Francesco Sergi & Davide Aloisio & Maurizio Cellura & Vincenzo Antonucci & Marco Ferraro, 2021. "A Review of Key Performance Indicators for Building Flexibility Quantification to Support the Clean Energy Transition," Energies, MDPI, vol. 14(18), pages 1-19, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5676-:d:632219
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    References listed on IDEAS

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    1. Dominković, D.F. & Dobravec, V. & Jiang, Y. & Nielsen, P.S. & Krajačić, G., 2018. "Modelling smart energy systems in tropical regions," Energy, Elsevier, vol. 155(C), pages 592-609.
    2. Cellura, Maurizio & Guarino, Francesco & Longo, Sonia & Mistretta, Marina, 2017. "Modeling the energy and environmental life cycle of buildings: A co-simulation approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 733-742.
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    Cited by:

    1. Awan, Muhammad Bilal & Sun, Yongjun & Lin, Wenye & Ma, Zhenjun, 2023. "A framework to formulate and aggregate performance indicators to quantify building energy flexibility," Applied Energy, Elsevier, vol. 349(C).
    2. Rafael E. Carrillo & Antonis Peppas & Yves Stauffer & Chrysa Politi & Tomasz Gorecki & Pierre-Jean Alet, 2022. "A Multilevel Control Approach to Exploit Local Flexibility in Districts Evaluated under Real Conditions," Energies, MDPI, vol. 15(16), pages 1-17, August.
    3. Piscitelli, Marco Savino & Giudice, Rocco & Capozzoli, Alfonso, 2024. "A holistic time series-based energy benchmarking framework for applications in large stocks of buildings," Applied Energy, Elsevier, vol. 357(C).
    4. Rusche, Simon & Weissflog., Jan & Wenninger, Simon & Häckel, Björn, 2023. "How flexible are energy flexibilities? Developing a flexibility score for revenue and risk analysis in industrial demand-side management," Applied Energy, Elsevier, vol. 345(C).
    5. Mark Kipngetich Kiptoo & Oludamilare Bode Adewuyi & Harun Or Rashid Howlader & Akito Nakadomari & Tomonobu Senjyu, 2023. "Optimal Capacity and Operational Planning for Renewable Energy-Based Microgrid Considering Different Demand-Side Management Strategies," Energies, MDPI, vol. 16(10), pages 1-25, May.
    6. Li, Han & Johra, Hicham & de Andrade Pereira, Flavia & Hong, Tianzhen & Le Dréau, Jérôme & Maturo, Anthony & Wei, Mingjun & Liu, Yapan & Saberi-Derakhtenjani, Ali & Nagy, Zoltan & Marszal-Pomianowska,, 2023. "Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives," Applied Energy, Elsevier, vol. 343(C).

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