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Proceedings of ASim Conference 2012: 1st Asia conference of IBPSA-China, Japan, Korea

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Building and System Level Sensitivity Analysis to U.S. DOE Commercial Reference Office Buildings in Different Climate Zones

KE XU, James Freihaut

Abstract: Dynamic whole building energy models (BEMs) are created for various reasons: to evaluate alternative design strategies; compliance checks with energy codes; apply certifications at the design stage of a new building; continuously improve building performance through its life cycle; assist decision making on implementation of energy conservation measures (ECMs). For quantitative guidance, BEM has to be carefully calibrated to reflect a building’s actual operation conditions. Given that even a simplified model would normally comprise hundreds of inputs, reconciling a specific BEM to a particular building system’s measured energy use is tedious, time-consuming, labour-intensive and without a guiding protocol methodology. Consequently, developing a concise list of parameters that have the greatest potential to impact the performance of critical building subsystems is the first and crucial stage in tuning a BEM. This study demonstrates a methodology of using prototyped, “newly constructed” medium office building EnergyPlus models, developed by U.S. Department of Energy (DOE), known as the DOE commercial reference buildings, with representative characteristics of numerous building types in U.S. market. By relating the reference buildings to the variety of existing building types in the U.S. building stock, these reference buildings serve as baseline models to establish a guiding parametric list. Key model input parameters are first selected by qualitatively analysing subsystem models. Each parameter is perturbed, while others remain unchanged relative to the base model values. The whole building annual energy use and subsystem energy use are outputted for each simulation run and compared to the baseline model results. After both building and subsystem level input-output sensitivity coefficients are calculated for each perturbation, all variables are prioritized according to the relative importance based on the degree of influence on outputs. Similar analyses are repeated in sixteen (16) cities/climate zones throughout U.S., generating the prioritized parameter lists for comparison. When tuning office building models with comparable size and system types in practice, those variables identified as having the greatest influence are earmarked to be validated through onsite measurement, sub-metering, or surveys. Such a prioritized key parameter list focuses designers’ attentions on the modelling assumptions or default values of * Corresponding author email: kzx100@psu.edu important variables that can lead to the discrepancies between simulated and actual building energy use.
Pages: 434 - 441
Paper:
asim2012_0057