A generalization approach for reduced order modelling of commercial buildings
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|Title:||A generalization approach for reduced order modelling of commercial buildings||Authors:||Shamsi, Mohammad Haris; Ali, Usman; O'Donnell, James||Permanent link:||http://hdl.handle.net/10197/10996||Date:||26-Jul-2019||Online since:||2019-08-20T07:05:19Z||Abstract:||Energy-efficient retrofits have become crucial in building sector as approximately 80% of buildings in developed countries are over 10 years old. Building simulation tools are now being used to provide estimates of energy consumption and implement various models which differ on the basis of enclosed details. Not all of these models are effective in terms of computation and the associated computational costs. This work devises a novel and generalized reduced-order grey-box modelling approach to predict the thermal behaviour of commercial buildings. The generalization approach reduces the order/complexity of model and lays out a general structure to obtain reduced-order models based on easily identifiable building metrics. We also implemented a forward-selection procedure to compare results obtained using a metrics-based approach. The network order obtained using metrics-based approach matches with the network order predicted by the forward selection procedure. The generalized structure would reduce the complexities involved in the dynamic simulation of urban building stock.||Funding Details:||Science Foundation Ireland||metadata.dc.description.othersponsorship:||ESIPP UCD||Type of material:||Journal Article||Publisher:||Informa UK Limited||Journal:||Journal of Building Performance Simulation||Start page:||1||End page:||16||Keywords:||Energy modelling; Reduced-order models; Commercial buildings; Thermal network RC models||DOI:||10.1080/19401493.2019.1641554||Language:||en||Status of Item:||Peer reviewed|
|Appears in Collections:||Mechanical & Materials Engineering Research Collection|
Energy Institute Research Collection
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