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Estimating the Smart Readiness Indicator in the Italian Residential Building Stock in Different Scenarios

Author

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  • Laura Canale

    (Department of Civil and Mechanical Engineering, University of Cassino and South Lazio, 03043 Cassino, Italy
    Faculty of Economy, Universitas Mercatorum, Piazza Mattei 10, 00186 Rome, Italy)

  • Marianna De Monaco

    (Department of Civil and Mechanical Engineering, University of Cassino and South Lazio, 03043 Cassino, Italy)

  • Biagio Di Pietra

    (Dipartimento Unità per l’Efficienza Energetica, Agenzia Nazionale per le Nuove Tecnologie, L’energia e lo Sviluppo Sostenibile (ENEA), Via Anguillarese, 301, 00123 Rome, Italy)

  • Giovanni Puglisi

    (Dipartimento Unità per l’Efficienza Energetica, Agenzia Nazionale per le Nuove Tecnologie, L’energia e lo Sviluppo Sostenibile (ENEA), Via Anguillarese, 301, 00123 Rome, Italy)

  • Giorgio Ficco

    (Department of Civil and Mechanical Engineering, University of Cassino and South Lazio, 03043 Cassino, Italy)

  • Ilaria Bertini

    (Dipartimento Unità per l’Efficienza Energetica, Agenzia Nazionale per le Nuove Tecnologie, L’energia e lo Sviluppo Sostenibile (ENEA), Via Anguillarese, 301, 00123 Rome, Italy)

  • Marco Dell’Isola

    (Department of Civil and Mechanical Engineering, University of Cassino and South Lazio, 03043 Cassino, Italy)

Abstract

The Energy Performance of Buildings Directive 2018/844/EU introduced the smart readiness indicator (SRI) to provide a framework to evaluate and promote building smartness in Europe. In order to establish a methodological framework for the SRI calculation, two technical studies were launched, at the end of which a consolidated methodology to calculate the SRI of a building basing on a flexible and modular multicriteria assessment has been proposed. In this paper the authors applied the above-mentioned methodology to estimate the SRI of the Italian residential building stock in different scenarios. To this end, eight “smart building typologies”, representative of the Italian residential building stock, have been identified. For each smart building typology, the SRI was calculated in three scenarios: (a) base scenario (building stock as it is); (b) an “energy scenario” (simple energy retrofit) and (c) a “smart energy scenario” (energy retrofit from a smart perspective). It was therefore possible to estimate a national average SRI value of 5.0%, 15.7%, and 27.5% in the three above defined scenarios, respectively.

Suggested Citation

  • Laura Canale & Marianna De Monaco & Biagio Di Pietra & Giovanni Puglisi & Giorgio Ficco & Ilaria Bertini & Marco Dell’Isola, 2021. "Estimating the Smart Readiness Indicator in the Italian Residential Building Stock in Different Scenarios," Energies, MDPI, vol. 14(20), pages 1-19, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:20:p:6442-:d:652131
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    References listed on IDEAS

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    1. Ballarini, Ilaria & Corgnati, Stefano Paolo & Corrado, Vincenzo, 2014. "Use of reference buildings to assess the energy saving potentials of the residential building stock: The experience of TABULA project," Energy Policy, Elsevier, vol. 68(C), pages 273-284.
    2. Ilaria Vigna & Roberta Pernetti & Giovanni Pernigotto & Andrea Gasparella, 2020. "Analysis of the Building Smart Readiness Indicator Calculation: A Comparative Case-Study with Two Panels of Experts," Energies, MDPI, vol. 13(11), pages 1-18, June.
    3. Liu, Yang & Yu, Nanpeng & Wang, Wei & Guan, Xiaohong & Xu, Zhanbo & Dong, Bing & Liu, Ting, 2018. "Coordinating the operations of smart buildings in smart grids," Applied Energy, Elsevier, vol. 228(C), pages 2510-2525.
    4. Elisa Conticelli & Gianluca Gobbi & Paula Isabella Saavedra Rosas & Simona Tondelli, 2021. "Assessing the Performance of Modal Interchange for Ensuring Seamless and Sustainable Mobility in European Cities," Sustainability, MDPI, vol. 13(2), pages 1-24, January.
    5. Paris A. Fokaides & Christiana Panteli & Andri Panayidou, 2020. "How Are the Smart Readiness Indicators Expected to Affect the Energy Performance of Buildings: First Evidence and Perspectives," Sustainability, MDPI, vol. 12(22), pages 1-12, November.
    6. Banister, David, 2008. "The sustainable mobility paradigm," Transport Policy, Elsevier, vol. 15(2), pages 73-80, March.
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    Cited by:

    1. Rosa Francesca De Masi & Gerardo Maria Mauro & Silvia Ruggiero & Francesca Villano, 2023. "Predicting Building Energy Demand and Retrofit Potentials Using New Climatic Stress Indices and Curves," Energies, MDPI, vol. 16(16), pages 1-23, August.

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