Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/191900
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dc.titleUncertainty analysis and parameter estimation of HVAC systems in building energy models
dc.contributor.authorAdrian Chong
dc.contributor.authorKhee Poh Lam
dc.date.accessioned2021-06-09T01:19:28Z
dc.date.available2021-06-09T01:19:28Z
dc.date.issued2015-01-01
dc.identifier.citationAdrian Chong, Khee Poh Lam (2015-01-01). Uncertainty analysis and parameter estimation of HVAC systems in building energy models. 14th IBPSA Building Simulation Conference : 2788-2795. ScholarBank@NUS Repository.
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/191900
dc.description.abstractBuilding performance simulation has the potential to quantitatively evaluate design alternatives and various energy conservation measures for retrofit projects. However before design strategies can be evaluated, accurate modeling of existing conditions is crucial. This paper extends current model calibration practice by presenting a probabilistic method for estimating uncertain parameters in HVAC systems for whole building energy modeling. Using Markov Chain Monte Carlo (MCMC) methods, probabilistic estimates of the parameters in two HVAC models were generated for use in EnergyPlus. Demonstrated through a case study, the proposed methodology provides predictions that more accurately match observed data than base case models that are developed using default values, typical assumptions and rules of thumb.
dc.description.urihttp://www.ibpsa.org/proceedings/BS2015/p2114.pdf
dc.publisherIBPSA
dc.sourceElements
dc.typeConference Paper
dc.date.updated2021-06-08T08:07:21Z
dc.contributor.departmentDEPT OF BUILDING
dc.description.sourcetitle14th IBPSA Building Simulation Conference
dc.description.page2788-2795
dc.published.statePublished
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