期刊
ADVANCES IN APPLIED ENERGY
卷 10, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.adapen.2023.100135
关键词
Building performance simulation; Performance-driven design; Operational optimization; Digital twin; Building-to-grid
As one of the most important technologies for carbon-mitigation in the building sector, building performance simulation (BPS) has played an increasingly important role with the support of building energy modelling (BEM) technology. This paper reviews the application of BEM at different scales and stages, providing insights into its objectives, frameworks, modelling methods, and applicability. The paper also discusses future research opportunities and recommendations for integrating BEM with other technologies.
As one of the most important and advanced technology for carbon-mitigation in the building sector, building performance simulation (BPS) has played an increasingly important role with the powerful support of building energy modelling (BEM) technology for energy-efficient designs, operations, and retrofitting of buildings. Owing to its deep integration of multi-disciplinary approaches, the researchers, as well as tool developers and practitioners, are facing opportunities and challenges during the application of BEM at multiple scales and stages, e.g., building/system/community levels and planning/design/operation stages. By reviewing recent studies, this paper aims to provide a clear picture of how BEM performs in solving different research questions on varied scales of building phase and spatial resolution, with a focus on the objectives and frameworks, modelling methods and tools, applicability and transferability. To guide future applications of BEM for performance-driven building energy management, we classified the current research trends and future research opportunities into five topics that span through different stages and levels: (1) Simulation for performance-driven design for new building and retrofit design, (2) Model-based operational performance optimization, (3) Integrated simulation using data measurements for digital twin, (4) Building simulation supporting urban energy planning, and (5) Modelling of building-to-grid interaction for demand response. Additionally, future research recommendations are discussed, covering potential applications of BEM through integration with occupancy and behaviour modelling, integration with machine learning, quantification of model uncertainties, and linking to building monitoring systems.
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