Abstract

According to the European Union, buildings account for 40% of overall energy use and 36% of CO2 emissions, with existing energy-inefficient buildings the main source of losses. Efforts to enhance the thermal comfortability of users in buildings can result in overheating if not appropriately designed, which in turn could lead to health issues as well as continual emission of greenhouse gases. To provide further insights into this dilemma and contribute to improving energy-efficient building designs, we undertake a new modeling technique encompassing a complete analysis of the existing building 3D model as well as solar radiation behavior on buildings. The technique involves 3D building information modeling (3D BIM) that is reconstructed using computer-aided design (CAD). Ladybug and Honeybee plugins for Grasshopper for Rhino are then used to evaluate environmental and building performance using the energy plus weather (EPW) file of Wuhan city, China, as a case study. An assessment of ‘with’ and ‘without’ built architectural surroundings contexts is also carried out in relation to summer and winter solstices. An overall change of approximately 29.56% is observed between ‘with’ and ‘without’ surrounding contexts, which suggests that both have a significant influence on the solar potential of individual buildings. Investigation of internal and external thermal energy consumption behaviors in relation to building comfort lead us to suggest an optimized smart solution which is validated using our case study site in Wuhan. Our findings suggest that the building energy lifespan can be increased while reducing environmental consequences if an estimated 50% of monthly energy savings are made. The findings of this study provide useful insights for decision-makers, engineers, and designers of energy-efficient buildings.

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Data Availability Statement

All data, models, and code generated or used during the study appear in the published article.

Acknowledgments

This study is supported by the National Key R&D Program of China (2016YFB0502203).

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Journal of Energy Engineering
Volume 149Issue 1February 2023

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Received: Apr 8, 2022
Accepted: Sep 24, 2022
Published online: Nov 28, 2022
Published in print: Feb 1, 2023
Discussion open until: Apr 28, 2023

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Hassan Waqas [email protected]
Ph.D. Candidate, National Engineering Research Center for Geographic Information System, School of Geography and Information Engineering, China Univ. of Geosciences, Wuhan 430074, China. Email: [email protected]
Jianga Shang [email protected]
Professor, National Engineering Research Center for Geographic Information System, School of Computer Science, China Univ. of Geosciences, Wuhan 430074, China (corresponding author). Email: [email protected]
Ph.D. Candidate, State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing (LIESMARS), Wuhan Univ., Wuhan 430079, China. Email: [email protected]
Safi Ullah, Ph.D. [email protected]
Dept. of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan Univ., Shanghai 200438, China. Email: [email protected]
Ph.D. Candidate, Ministry of Education, School of Geosciences and Info-Physics, Central South Univ., Changsha 410083, China. Email: [email protected]
Ph.D. Candidate, Institute of Natural Disaster Research, School of Environment, Northeast Normal Univ., Changchun 130024, China. ORCID: https://orcid.org/0000-0002-5132-0798. Email: [email protected]
Dept. of Mining and Petroleum Engineering, Faculty of Engineering, Al-Azhar Univ., Cairo 11884, Egypt. ORCID: https://orcid.org/0000-0003-1009-6459. Email: [email protected]
National Institute of Water and Atmospheric Research (NIWA Taihoro Nukurangi), Riccarton, Christchurch 8440, New Zealand. ORCID: https://orcid.org/0000-0003-3986-612X. Email: [email protected]

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