• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.3
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• pp.103-111
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• 2018

A prototypical building that represents the energy characteristics of buildings can be used as a mean of improving building energy efficiency by supporting policy makers, researchers, architects and engineers. This paper is a fundamental study for the definition of prototypical office building models of Korea. First of all, the term "prototypical buildings" was defined in the context of the representatives of building stock by examining the meanings used from many previous researches. Then, building energy related DB of Korea that is available from public and governmental organization such as MLIT (Ministry of Land, Infrastructure and Transport) and KEEI (Korea Energy Economics Institute) is analyzed in terms of materials for prototypical building definition. Finally, numerous prototypical building studies since 1990's from all of the world were classified with three criteria based on the degrees of the used DB and assumptions in defining prototypical building. The found three criteria are EDPB (Empirical Decision based Prototypical Building), HIPB (Hybrid Information based Prototypical Building) SAPB (Statistical Analysis based Prototypical Building).

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.17 no.1
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• pp.1-13
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• 2021

Before newly-built building and building remodeling, it is important to predict and analyze building energy performance through energy simulation programs. Nevertheless, simulation results widely vary depending on individual user experience and input values. Therefore, this study uses prototypical building model, a versatile tool in building energy modeling, simulation and research for researchers and policy-makers, and ASHRAE standards. Then, it analyzed the changes in design type (roof type, number of floors) for the base case. As the result, it was found that the gap of annual energy demand per between them is maximally 9.1%.

• Land and Housing Review
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• v.15 no.2
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• pp.9-17
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• 2024

The prototypical building energy model is very useful in building energy policies, research, and technology development. A prototypical apartment model for detailed energy analysis was proposed by Seo et al. in 2014, but sufficient verification was not possible due to the lack of reliable measurement data in predicting the model's energy consumption. However, verification is now possible thanks to a recent study that analyzed the Household Energy Panel Survey (HEPS) data that is released annually by the Korea Energy Economics Institute (KEEI) and published apartment complex benchmark data. The data was used to calibrate the prototypical apartment energy model located in the central region and constructed between 1990 and 1999. The calibrated model was used to verify the other apartment building groups with respect to region and year of completion. Meteorological data for five representative cities each in the central and southern regions were used for the simulation. A majority of the 18 groups produced results that satisfied the MBE and cv(RMSE) criteria.

• Journal of the Korean Solar Energy Society
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• v.22 no.4
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• pp.68-76
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• 2002

This paper discusses thermal and ventilation performance which might be caused by the adoption of one of specific building facade techniques, Double Skin System(DSS). One building with a prototypical DSS was selected and systematically investigated through field monitoring and computer simulation techniques. A network model of ventilation was successfully made using COMIS to evaluate ventilation performance of the system which can hardly be done by field measurements. Various operating conditions of air conditioning on/off and window opening were implemented in this type of building. Through the appropriate operation of the DSS in summer, simulation-based and experimental results implicate that it can lead to cooling energy savings.

• Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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• v.12 no.6
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• pp.627-640
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• 2018

Submetering electricity consumption data enables more detail input of end use components, such as lighting, plug, HVAC, and occupancy in building energy modeling. However, such an modeling efforts and results are rarely tried and published in terms of the estimation accuracy of electricity demand. In this research, actual submetering data obtained from a university building is analyzed and provided for building energy modeling practice. As alternative modeling cases, conventional modeling method (Case-1), using reference schedule per building usage, and main metering data based modeling method (Case-2) are established. Detail efforts are added to derive prototypical schedules from the metered data by introducing variability index. The simulation results revealed that Case-1 showed the largest error as we can expect. And Case-2 showed comparative error relative to Case-3 in terms of total electricity estimation. But Case-2 showed about two times larger error in CV (RMSE) in lighting energy demand due to lack of End Use consumption information.

• Journal of the Korean Solar Energy Society
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• v.36 no.6
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• pp.37-46
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• 2016

In this study, long-term global illuminance data for 19 selected cities are calculated from modeled solar radiation data, AEER's TMY2. Perez model in Daysim daylight simulation tool is used for the solar radiation to illuminance conversion. And then, daylight availability in an unit office space is evaluated for the 19 cities. For this evaluation, various daylight performance indices are reviewed since static daylight performance index such as daylight factor (DF) and annual average global illuminance value is not suitable for actual performance evaluation in terms of visual comfort and light energy saving of a space. This study evaluated daylighting performance of prototypical office space module by introducing DA (daylight autonomy) and UDI (Useful Daylight Illuminance) index for major cities of Korea. Result shows that there is upto 18% of illuminance level difference with annual average global illuminance data, but if we consider useful daylight in a space the illuminance level difference among the cities are only within 5%. This means that for sustainable building design especially in daylight design, amount of annual global illuminance is not important factor even in cloudy cities. Daylight design and daylight harvesting system would return similar energy saving impact regardless of building location.