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Energy Use in Residential Buildings: Impact of Building Automation Control Systems on Energy Performance and Flexibility

Author

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  • Francesco Mancini

    (Department of Planning, Design and Technology of Architecture, Sapienza University of Rome, 00197 Rome, Italy)

  • Gianluigi Lo Basso

    (Department of Astronautics, Electrical Energy Engineering, Sapienza University of Rome, 00184 Rome, Italy)

  • Livio de Santoli

    (Department of Astronautics, Electrical Energy Engineering, Sapienza University of Rome, 00184 Rome, Italy)

Abstract

This work shows the results of a research activity aimed at characterizing the energy habits of Italian residential users. In detail, by the energy simulation of a buildings sample, the opportunity to implement a demand/response program (DR) has been investigated. Italian residential utilities are poorly electrified and flexible loads are low. The presence of an automation system is an essential requirement for participating in a DR program and, in addition, it can allow important reductions in energy consumption. In this work the characteristics of three control systems have been defined, based on the services incidence on energy consumptions along with a sensitivity analysis on some energy drivers. Using the procedure established by the European Standard EN 15232, the achievable energy and economic savings have been evaluated. Finally, a financial analysis of the investments has been carried out, considering also the incentives provided by the Italian regulations. The payback time is generally not very long: depending on the control system features it varies from 7 to 10 years; moreover, the automation system installation within dwellings is a relatively simple activity, which is characterized by a limited execution times and by an initial expenditure ranging in 1000 € to 4000 €, related to the three sample systems.

Suggested Citation

  • Francesco Mancini & Gianluigi Lo Basso & Livio de Santoli, 2019. "Energy Use in Residential Buildings: Impact of Building Automation Control Systems on Energy Performance and Flexibility," Energies, MDPI, vol. 12(15), pages 1-21, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:2896-:d:252296
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    References listed on IDEAS

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    1. Zhou, Bin & Li, Wentao & Chan, Ka Wing & Cao, Yijia & Kuang, Yonghong & Liu, Xi & Wang, Xiong, 2016. "Smart home energy management systems: Concept, configurations, and scheduling strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 30-40.
    2. 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.
    3. Chen, Yujiao & Tong, Zheming & Wu, Wentao & Samuelson, Holly & Malkawi, Ali & Norford, Leslie, 2019. "Achieving natural ventilation potential in practice: Control schemes and levels of automation," Applied Energy, Elsevier, vol. 235(C), pages 1141-1152.
    4. Mustafa Alparslan Zehir & Kadir Baris Ortac & Hakan Gul & Alp Batman & Zafer Aydin & João Carlos Portela & Filipe Joel Soares & Mustafa Bagriyanik & Unal Kucuk & Aydogan Ozdemir, 2019. "Development and Field Demonstration of a Gamified Residential Demand Management Platform Compatible with Smart Meters and Building Automation Systems," Energies, MDPI, vol. 12(5), pages 1-18, March.
    5. Lusis, Peter & Khalilpour, Kaveh Rajab & Andrew, Lachlan & Liebman, Ariel, 2017. "Short-term residential load forecasting: Impact of calendar effects and forecast granularity," Applied Energy, Elsevier, vol. 205(C), pages 654-669.
    6. Francesco Mancini & Gianluigi Lo Basso & Livio De Santoli, 2019. "Energy Use in Residential Buildings: Characterisation for Identifying Flexible Loads by Means of a Questionnaire Survey," Energies, MDPI, vol. 12(11), pages 1-19, May.
    7. Salvatore Favuzza & Mariano Giuseppe Ippolito & Fabio Massaro & Rossano Musca & Eleonora Riva Sanseverino & Giuseppe Schillaci & Gaetano Zizzo, 2018. "Building Automation and Control Systems and Electrical Distribution Grids: A Study on the Effects of Loads Control Logics on Power Losses and Peaks," Energies, MDPI, vol. 11(3), pages 1-15, March.
    8. Severin Beucker & Joseph D. Bergesen & Thomas Gibon, 2016. "Building Energy Management Systems: Global Potentials and Environmental Implications of Deployment," Journal of Industrial Ecology, Yale University, vol. 20(2), pages 223-233, April.
    9. Bhati, Abhishek & Hansen, Michael & Chan, Ching Man, 2017. "Energy conservation through smart homes in a smart city: A lesson for Singapore households," Energy Policy, Elsevier, vol. 104(C), pages 230-239.
    10. Francesco Mancini & Benedetto Nastasi, 2019. "Energy Retrofitting Effects on the Energy Flexibility of Dwellings," Energies, MDPI, vol. 12(14), pages 1-19, July.
    11. Aydin, Erdal & Brounen, Dirk, 2019. "The impact of policy on residential energy consumption," Energy, Elsevier, vol. 169(C), pages 115-129.
    12. Aste, Niccolò & Manfren, Massimiliano & Marenzi, Giorgia, 2017. "Building Automation and Control Systems and performance optimization: A framework for analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 313-330.
    13. He, Xian & Keyaerts, Nico & Azevedo, Isabel & Meeus, Leonardo & Hancher, Leigh & Glachant, Jean-Michel, 2013. "How to engage consumers in demand response: A contract perspective," Utilities Policy, Elsevier, vol. 27(C), pages 108-122.
    14. Wu, Zhou & Wang, Bo & Xia, Xiaohua, 2016. "Large-scale building energy efficiency retrofit: Concept, model and control," Energy, Elsevier, vol. 109(C), pages 456-465.
    15. Laes, Erik & Mayeres, Inge & Renders, Nele & Valkering, Pieter & Verbeke, Stijn, 2018. "How do policies help to increase the uptake of carbon reduction measures in the EU residential sector? Evidence from recent studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 234-250.
    16. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    17. Kylili, Angeliki & Fokaides, Paris A. & Lopez Jimenez, Petra Amparo, 2016. "Key Performance Indicators (KPIs) approach in buildings renovation for the sustainability of the built environment: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 906-915.
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    Cited by:

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    4. Francesco Mancini & Sabrina Romano & Gianluigi Lo Basso & Jacopo Cimaglia & Livio de Santoli, 2020. "How the Italian Residential Sector Could Contribute to Load Flexibility in Demand Response Activities: A Methodology for Residential Clustering and Developing a Flexibility Strategy," Energies, MDPI, vol. 13(13), pages 1-25, July.
    5. Andrzej Ożadowicz, 2022. "A Hybrid Approach in Design of Building Energy Management System with Smart Readiness Indicator and Building as a Service Concept," Energies, MDPI, vol. 15(4), pages 1-19, February.
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    9. Francesco Mancini & Jacopo Cimaglia & Gianluigi Lo Basso & Sabrina Romano, 2021. "Implementation and Simulation of Real Load Shifting Scenarios Based on a Flexibility Price Market Strategy—The Italian Residential Sector as a Case Study," Energies, MDPI, vol. 14(11), pages 1-21, May.
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    12. Athila Santos & Na Liu & Muhyiddine Jradi, 2021. "AUSTRET: An Automated Step Response Testing Tool for Building Automation and Control Systems," Energies, MDPI, vol. 14(13), pages 1-20, July.

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