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Analysis of EnergyPlus for use in residential building energy optimization

Posted on:2011-06-01Degree:M.SType:Thesis
University:University of Colorado at BoulderCandidate:Spencer, Justin SFull Text:PDF
GTID:2442390002463360Subject:Engineering
Abstract/Summary:
This work explored the utility of EnergyPlus as a simulation engine for doing residential building energy optimization, with the objective of finding the modeling areas that require further development in EnergyPlus for residential optimization applications. This work was conducted primarily during 2006-2007, with publication occurring later in 2010. The assessments and recommendations apply to the simulation tool versions available in 2007.;During this work, an EnergyPlus v2.0 (2007) input file generator was developed for use in BEopt 0.8.0.4 (2007). BEopt 0.8.0.4 is a residential Building Energy optimization program developed at the National Renewable Energy Laboratory in Golden, Colorado.;Residential modeling capabilities of EnergyPlus v2.0 were scrutinized and tested. Modeling deficiencies were identified in a number of areas. These deficiencies were compared to deficiencies in the DOE2.2 V44E4(2007)/TRNSYS simulation engines. The highest priority gaps in EnergyPlus v2.0's residential modeling capability are in infiltration, duct leakage, and foundation modeling.;Optimization results from DOE2.2 V44E4 and EnergyPlus v2.0 were analyzed to search for modeling differences that have a significant impact on optimization results. Optimal buildings at different energy savings levels were compared to look for biases. It was discovered that the EnergyPlus v2.0 optimizations consistently chose higher wall insulation levels than the DOE2.2 V44E4 optimizations. The points composing the optimal paths chosen by DOE2.2 V44E4 and EnergyPlus v2.0 were compared to look for points chosen by one optimization that were significantly different from the other optimal path. These outliers were compared to consensus optimal points to determine the simulation differences that cause disparities in the optimization results. The differences were primarily caused by modeling of window radiation exchange and HVAC autosizing.
Keywords/Search Tags:Optimization, Residential building energy, Energyplus, Modeling, Simulation, V44E4
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