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Energy Transition: Semi-Automatic BIM Tool Approach for Elevating Sustainability in the Maputo Natural History Museum

Author

Listed:
  • Giuseppe Piras

    (Department of Astronautical, Electrical and Energy Engineering (DIAEE), Sapienza University of Rome, 00184 Roma, Italy)

  • Francesco Muzi

    (Department of Astronautical, Electrical and Energy Engineering (DIAEE), Sapienza University of Rome, 00184 Roma, Italy)

Abstract

Mozambique is experiencing the consequences of a severe energy crisis with economic and social impacts. Its strict dependence on hydroelectric sources is being severely tested by recent droughts that have drastically reduced water levels in dams. However, Mozambique is addressing energy poverty by exploring renewable energy sources thanks to investments in the sector by the European Union. The research concerns an energy analysis profile of the country and the penetration of renewable energy, presenting an energy upgrading scope through a semi-automatic calculation methodology in a Building Information Modeling (BIM) environment. The building under study, located in Maputo, is the Natural History Museum, which plays an important role in biodiversity conservation. Therefore, this paper proposes a BIM methodology for sizing an environmental control system tailored to serve the museum. The proposed system replaces the previous one and includes a photovoltaic system that not only meets the museum’s load but also supplies electricity to the surrounding area. Energy production from renewable sources with a surplus of 30% has been achieved. The proposed digital methodology has identified a maximum gap of 1.5% between the dimensions of the BIM duct and those of a traditional plant design, meeting ASHRAE requirements for environmental control.

Suggested Citation

  • Giuseppe Piras & Francesco Muzi, 2024. "Energy Transition: Semi-Automatic BIM Tool Approach for Elevating Sustainability in the Maputo Natural History Museum," Energies, MDPI, vol. 17(4), pages 1-22, February.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:4:p:775-:d:1334327
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    References listed on IDEAS

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    1. Giuseppe Piras & Francesco Muzi & Zahra Ziran, 2024. "Open Tool for Automated Development of Renewable Energy Communities: Artificial Intelligence and Machine Learning Techniques for Methodological Approach," Energies, MDPI, vol. 17(22), pages 1-16, November.

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