A 10-Year Review of the Semantic Web Technology Applications in Building Energy Reductions

Xiaoyue Yi, Llewellyn Tang (), Mengtian Yin and Haotian Li
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Xiaoyue Yi: The University of Hong Kong
Llewellyn Tang: The University of Hong Kong
Mengtian Yin: The University of Hong Kong
Haotian Li: The University of Hong Kong

A chapter in Proceedings of the 27th International Symposium on Advancement of Construction Management and Real Estate, 2023, pp 150-163 from Springer

Abstract: Abstract Energy consumptions due to buildings account for around 1/3 of the global energy consumptions, which addresses the importance of reducing energy uses in buildings. In the age of big data, the digitalization process is helping the energy savings in the building industry. However, semantic interoperability between data in multiple systems/software is lacking, which hinders green building design and operation management. Semantic Web technologies (SWT), connecting machine-readable concepts that characterize real-world objects, are beneficial for representing and reasoning the data in building energy savings. This study aimed at reviewing the related works from 2011 to 2022 which were relevant to the applications of SWT in the reduction of building energy. Reviewed studies were categorized into 3 groups which were reducing energy loads during the design processes, applying renewable energy in buildings, and energy-efficient building systems. The applications of SWT utilizations of energy savings in building designs and system operations were reviewed. SWT is found beneficial to energy saving because it helps organize resources, supports the decision-making processes, improves design and management efficiency, facilitates querying and interoperability, and assists big data analysis. With the assistance of SWT, building energy could be saved by 2.11% to 40% according to the results of the literature. The SWT-based studies in the field of reducing building energy are still in their infancy. Further studies might focus on more SWT utilizations of building lifecycle for energy reductions, extending ontologies to more building systems and types, more complex HVAC control and FDD, and more energy analysis tools.

Keywords: Semantic Web Technologies (SWT); Building Energy Reductions; Sustainable Designs; Renewable Energy; Building Systems (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-981-99-3626-7_12

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