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Building Energy Simulations Based on Weather Forecast Meteorological Model: The Case of an Institutional Building in Greece

Author

Listed:
  • Effrosyni Giama

    (Process Equipment Design Laboratory, Department of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Georgios Chantzis

    (Process Equipment Design Laboratory, Department of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Serafim Kontos

    (Laboratory of Atmospheric Physics, Department of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Stavros Keppas

    (Laboratory of Atmospheric Physics, Department of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Anastasia Poupkou

    (Research Centre for Atmospheric Physics and Climatology, Academy of Athens, 10680 Athens, Greece)

  • Natalia Liora

    (Laboratory of Atmospheric Physics, Department of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Dimitrios Melas

    (Laboratory of Atmospheric Physics, Department of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

Abstract

The vision of decarbonization creates the need to design and construct even more energy-efficient buildings. This current target is even more compelling and challenging. The main issue when designing energy-efficient buildings is to identify present and future building energy requirements. A trending method for solving this problem is dynamic building energy simulation. One of the main inputs during energy simulation is weather data. However, the real problem lies in the fact that standard weather data are good at defining the present situation, and they help in designing buildings that behave efficiently under current climate conditions. To achieve the goal of constructing climate proof buildings, the Weather Research and Forecast meteorological model (WRF) was used to predict future climate scenarios. At first, data from previous years (2006–2010) were used to represent the current climate. The model was used to generate future climate data. Thus, results were produced for 5 year periods 2046–2050 and 2096–2100. These data were used for the energy simulation of an office building in Thessaloniki, Greece. The simulation results showed a reduction in heating loads by approximately 20% in the long term and a simultaneous impressive increase in cooling loads by 60%, highlighting the inadequacy of the existing building shell, as well as the heating, ventilation, and air-conditioning (HVAC) system design.

Suggested Citation

  • Effrosyni Giama & Georgios Chantzis & Serafim Kontos & Stavros Keppas & Anastasia Poupkou & Natalia Liora & Dimitrios Melas, 2022. "Building Energy Simulations Based on Weather Forecast Meteorological Model: The Case of an Institutional Building in Greece," Energies, MDPI, vol. 16(1), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:191-:d:1013777
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    References listed on IDEAS

    as
    1. Giannaros, Theodore M. & Melas, Dimitrios & Ziomas, Ioannis, 2017. "Performance evaluation of the Weather Research and Forecasting (WRF) model for assessing wind resource in Greece," Renewable Energy, Elsevier, vol. 102(PA), pages 190-198.
    2. Moazami, Amin & Nik, Vahid M. & Carlucci, Salvatore & Geving, Stig, 2019. "Impacts of future weather data typology on building energy performance – Investigating long-term patterns of climate change and extreme weather conditions," Applied Energy, Elsevier, vol. 238(C), pages 696-720.
    3. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2017. "Potential impacts of climate change on European wind energy resource under the CMIP5 future climate projections," Renewable Energy, Elsevier, vol. 101(C), pages 29-40.
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    1. Tamás Storcz & Zsolt Ercsey & Kristóf Roland Horváth & Zoltán Kovács & Balázs Dávid & István Kistelegdi, 2023. "Energy Design Synthesis: Algorithmic Generation of Building Shape Configurations," Energies, MDPI, vol. 16(5), pages 1-17, February.

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