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Innovative Renewable Technology Integration for Nearly Zero-Energy Buildings within the Re-COGNITION Project

Author

Listed:
  • Giulia Mancò

    (Department of Energy, Politecnico di Torino, 10129 Torino, Italy)

  • Elisa Guelpa

    (Department of Energy, Politecnico di Torino, 10129 Torino, Italy)

  • Alessandro Colangelo

    (Department of Energy, Politecnico di Torino, 10129 Torino, Italy)

  • Alessandro Virtuani

    (École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland)

  • Tommaso Morbiato

    (WindCity Srl, 38068 Rovereto, Italy)

  • Vittorio Verda

    (Department of Energy, Politecnico di Torino, 10129 Torino, Italy)

Abstract

With the 2010/31/EU directive, all new buildings shall be nearly zero-energy buildings (nZEB) from 2020 onward, with the aim of strongly reducing the energy consumption related to the building sector. To achieve this goal, it is not sufficient to focus on the design of the building envelope; smart and efficient energy management is necessary. Moreover, to ensure the adoption of RES systems in the built environment, innovative technologies need to be further developed in order to increase their cost-effectiveness, energy efficiency and integration capability. This paper proposes a synthesis, design and operation optimization of an integrated multi-energy system composed of traditional and innovative renewable technologies, developed within the European project Re-COGNITION. A biogas-based micro cogeneration unit, lightweight glass-free photovoltaic modules, a passive variable geometry small wind turbine optimized for an urban environment and latent heat thermal storage based on phase change materials are some of the technologies developed within the Re-COGNITION project. The optimization problem is solved to contemporarily evaluate (a) the optimal design and (b) the optimal operations of the set of technologies considering both investment and operating costs, using mixed integer non-linear programming. The optimization is applied to the four pilots that are developed during the project, in various European cities (Turin (Italy), Corby (United Kingdom), Thessaloniki (Greece), Cluj-Napoca (Romania). Simulation results show that the development and optimal exploitation of new technologies through optimization strategies provide significant benefits in terms of cost (between 11% and 42%) and emissions (between 10% and 25%), managing building import/export energy and charge/discharge storage cycles.

Suggested Citation

  • Giulia Mancò & Elisa Guelpa & Alessandro Colangelo & Alessandro Virtuani & Tommaso Morbiato & Vittorio Verda, 2021. "Innovative Renewable Technology Integration for Nearly Zero-Energy Buildings within the Re-COGNITION Project," Sustainability, MDPI, vol. 13(4), pages 1-24, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:1938-:d:497626
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    References listed on IDEAS

    as
    1. Ashouri, Araz & Fux, Samuel S. & Benz, Michael J. & Guzzella, Lino, 2013. "Optimal design and operation of building services using mixed-integer linear programming techniques," Energy, Elsevier, vol. 59(C), pages 365-376.
    2. Méndez Echenagucia, Tomás & Capozzoli, Alfonso & Cascone, Ylenia & Sassone, Mario, 2015. "The early design stage of a building envelope: Multi-objective search through heating, cooling and lighting energy performance analysis," Applied Energy, Elsevier, vol. 154(C), pages 577-591.
    3. Strantzali, Eleni & Aravossis, Konstantinos, 2016. "Decision making in renewable energy investments: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 885-898.
    4. Diakaki, Christina & Grigoroudis, Evangelos & Kabelis, Nikos & Kolokotsa, Dionyssia & Kalaitzakis, Kostas & Stavrakakis, George, 2010. "A multi-objective decision model for the improvement of energy efficiency in buildings," Energy, Elsevier, vol. 35(12), pages 5483-5496.
    5. Lu, Yuehong & Wang, Shengwei & Sun, Yongjun & Yan, Chengchu, 2015. "Optimal scheduling of buildings with energy generation and thermal energy storage under dynamic electricity pricing using mixed-integer nonlinear programming," Applied Energy, Elsevier, vol. 147(C), pages 49-58.
    6. Zhang, Sheng & Huang, Pei & Sun, Yongjun, 2016. "A multi-criterion renewable energy system design optimization for net zero energy buildings under uncertainties," Energy, Elsevier, vol. 94(C), pages 654-665.
    7. Arcuri, P. & Florio, G. & Fragiacomo, P., 2007. "A mixed integer programming model for optimal design of trigeneration in a hospital complex," Energy, Elsevier, vol. 32(8), pages 1430-1447.
    8. Eicker, Ursula & Pietruschka, Dirk & Haag, Maximilian & Schmitt, Andreas, 2015. "Systematic design and analysis of solar thermal cooling systems in different climates," Renewable Energy, Elsevier, vol. 80(C), pages 827-836.
    9. Mazzoni, Stefano & Ooi, Sean & Nastasi, Benedetto & Romagnoli, Alessandro, 2019. "Energy storage technologies as techno-economic parameters for master-planning and optimal dispatch in smart multi energy systems," Applied Energy, Elsevier, vol. 254(C).
    10. Zakeri, Behnam & Syri, Sanna, 2015. "Electrical energy storage systems: A comparative life cycle cost analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 569-596.
    11. Shaterabadi, Mohammad & Jirdehi, Mehdi Ahmadi & Amiri, Nima & Omidi, Sina, 2020. "Enhancement the economical and environmental aspects of plus-zero energy buildings integrated with INVELOX turbines," Renewable Energy, Elsevier, vol. 153(C), pages 1355-1367.
    12. Li, Hangxin & Wang, Shengwei, 2019. "Coordinated optimal design of zero/low energy buildings and their energy systems based on multi-stage design optimization," Energy, Elsevier, vol. 189(C).
    13. Perera, A.T.D. & Attalage, R.A. & Perera, K.K.C.K. & Dassanayake, V.P.C., 2013. "Designing standalone hybrid energy systems minimizing initial investment, life cycle cost and pollutant emission," Energy, Elsevier, vol. 54(C), pages 220-230.
    14. Maria Ferrara & Valentina Monetti & Enrico Fabrizio, 2018. "Cost-Optimal Analysis for Nearly Zero Energy Buildings Design and Optimization: A Critical Review," Energies, MDPI, vol. 11(6), pages 1-32, June.
    15. Kheiri, Farshad, 2018. "A review on optimization methods applied in energy-efficient building geometry and envelope design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 92(C), pages 897-920.
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    2. Paolo Bragolusi & Chiara D’Alpaos, 2021. "The Willingness to Pay for Residential PV Plants in Italy: A Discrete Choice Experiment," Sustainability, MDPI, vol. 13(19), pages 1-13, September.

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