Abstract
The aim of this paper is to propose a novel building information model (BIM)–building performance model (BPM)–building environmental model (BEM) framework to identify the most energy-efficient and cost-effective strategies for the renovation of existing education buildings to achieve the nearly zero-energy goal while minimizing the environmental impact. A case building, the University of Maryland’s Architecture Building, was used to demonstrate the validity of the framework and a set of building performance indicators—including energy performance, environmental impacts, and occupant satisfaction—were used to evaluate renovation strategies. Additionally, this novel framework further demonstrated the interoperability among different digital tools and platforms. Lastly, following a detailed analysis and measurements, the case study results highlighted a particular energy profile as well as the retrofit needs of education buildings. Eight different renovation packages were analyzed with the top-ranking package indicating an energy saving of 62%, carbon emissions reduction of 84%, and long-term cost savings of 53%, albeit with a relatively high initial cost. The most preferable package ranked second in all categories, with a moderate initial cost.
Highlights
This paper presented a novel building information model (BIM)–building performance model (BPM)–building environmental model (BEM) framework tailored toward education building renovation
It aimed to select suitable renovation strategies that take into account all performance indicators: an energy consumption reduction, CO2 emissions reduction, environmental impact reduction, and indoor quality improvement
The data derived from field measurements was cross-referenced with a post-occupancy survey and infrared thermography scan to create an accurate building profile and BIM model
Summary
Education buildings have a unique energy profile that differs from that of a typical nonresidential building (refer to Figures 1 and 2). Survey (CBECS) data, in education buildings, space heating accounts for 36% of the overall energy consumption (higher than in typical nonresidential buildings, at 25%), followed by cooling (11%) and computers (9%). The three major differences between a typical nonresidential building and education building are space heating, computing, and cooking. An education building has significantly less space heating and cooking energy demand, but it has a higher computing energy demand than that of nonresidential buildings. Cooking in education buildings accounts for 7%, while in a typical commercial office building, the energy spent on cooking is close to 0%. The differences between education buildings and typical non-commercial buildings may be attributed to the former’s unique operation schedule and varied user groups
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