• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.625-632
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• 2018

This study was done to reduce total energy demand based on resource shortage problems and to provide improvement points for more efficient adjustment of the high insulation standards for saving energy in Korea. The demand sensitivity was fully considered by varying the slope of each building. The energy performance of the building was maximized by the introduction of outdoor air at night. A final low-energy building model was developed with the two measures combined, and the short-term operation of the night-fuzzy ventilation system was simulated. The result showed a reduction of about 6 to 7 percent compared to the base model. The results could have many implications in terms of the need to conduct demand sensitivity analyses in architectural design.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.42 no.5
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• pp.28-38
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• 2013

• The Journal of Bigdata
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• v.6 no.1
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• pp.127-132
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• 2021

Korea is both a resource-poor country and a energy-consuming country. In addition, the use and dependence on electricity is very high, and more than 20% of total energy use is consumed in buildings. As research on deep learning and machine learning is active, research is underway to apply various algorithms to energy efficiency fields, and the introduction of building energy management systems (BEMS) for efficient energy management is increasing. In this paper, we constructed a database based on energy usage by device per household directly collected using smart plugs. We also implement algorithms that effectively analyze and predict the data collected using RNN and LSTM models. In the future, this data can be applied to analysis of power consumption patterns beyond prediction of energy consumption. This can help improve energy efficiency and is expected to help manage effective power usage through prediction of future data.

• Solar Energy
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• v.12 no.1
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• pp.72-80
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• 1992

This paper is concerned with the accurate estimation of the thermal mass effect on the variation of indoor temperature for residential buildings. To carry out the analysis here, the method called "PSTAR(Primary and Secondary Terms Analysis and Renormalization)" has been extensively used. This method was originally developed by the National Renewable Energy Laboratory(NREL) in the United States. The test results reported here represent two extreme cases of the interior thermal mass, which demonstrate its effect on the interior thermal environment as well as on the overall thermal behavior of the building structure. The monthly heating and cooling loads are also extrapolated by using the renormalized model, which are crucial in designing and refurbishing HVAC systems for the building.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.3-12
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• 2012

The slowdown of private building industry resulted in growth of remodeling market as a way to improve energy performance. Remodeling is considered more cost-effective and eco-friendly approach for energy efficient building than new construction. Since 2008, Seoul has promoted Building Retrofit Project (BRP) preponderantly to attract energy-saving renovation by supporting building owners to switch building system into energy-saving system when they remodel their old buildings. According to 2012 press release, 254 Private sectors participated in this green building project and annually reduced 41000ton of greenhouse gas emission, 14000TOE, which also result in 7.5 billion won energy cost savings per year. The paper focuses on the building envelope remodeling as a way to improve energy efficiency. Different components of the building envelope such as wall insulation, window, and shading, were applied to the baseline model and the comparison was analyzed to come up with the ideal solution. This study only assesses the building envelope as to suggest the way to redesign the better energy performing building. Offering solution focusing on the architectural feature is essential because it will provide basic information and standard when remodeling a building for energy efficiency, especially, for the nonresidential buildings used as rental offices.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1540-1547
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• 2013

The energy economic analysis of the standard rural house model with PV system was performed based on annual energy demand calculation using the EnergyPlus to contribute in reducing building energy which occupies 25% of national energy consumption and in developing a low-energy & eco-friendly house model. Two types of PV system installation was considered to cover electricity demand for cooling, electric, and heating devices. For the selected house model, heating energy demand is 7 times higher than cooling energy demand. For the Case1, it is favorable to use electricity from PV system for cooling and electric devices and to sell surplus electricity. For the Case2, it is favorable to use electricity from PV system for cooling, electricity and heating devices and to sell surplus electricity. Considering the installation cost of PV system and heat pump air conditioning system, the break-even point of Case1 and Case2 are about 13 and 11 years respectively. Although the installation cost of Case2 is more expensive, Case2 provides three times more profit than Case1 after the break-even point. Because the expected average life time of the selected PV system is 25 years, Case2 is more favorable option for the given standard rural house model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.223-233
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• 2021

Systematic and continuous monitoring and management of the energy consumption of buildings are important for estimating building energy efficiency, and ultimately aim to cope with climate change and establish effective policies for environment, and energy supply and demand policies. Globally, buildings consume 36% of total energy and account for 39% of carbon dioxide emissions. The purpose of this study is to generate three-dimensional thermo-spatial building models with photogrammetric technique using drone TIR (Thermal Infrared) images to measure the temperature emitted from a building, that is essential for the building energy rating system. The aerial triangulation was performed with both optical and TIR images taken from the sensor mounted on the drone, and the accuracy of the models was analyzed. In addition, the thermo-spatial models of temperature distribution of the buildings in three-dimension were visualized. Although shape of the objects 3D building modeling is relatively inaccurate as the spatial and radiometric resolution of the TIR images are lower than that of optical images, TIR imagery could be used effectively to measure the thermal energy of the buildings based on spatial information. This paper could be meaningful to present extension of photogrammetry to various application. The energy consumption could be quantitatively estimated using the temperature emitted from the individual buildings that eventually would be uses as essential information for building energy efficiency rating system.

• Journal of Energy Engineering
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• v.24 no.1
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• pp.69-77
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• 2015

The PMV regression analysis was conducted for this model based on a database of the PMV variables. PMV regression model simplification was completed through sensitivity and data analysis. The simplified PMV regression model's and Fanger PMV model was confirmed through MAE and RMSE. And the EMS in EnergyPlus was used to establish a simplified PMV regression analysis-based thermal comfort control. Also, the thermal comfort controls based on simplified PMV model and the Fanger PMV model were applied to the building model, it was confirmed that both controls met the thermal comfort range in more than 90% of cases during the air conditioning period.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.6
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• pp.1-8
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• 2005

The quantity of light available for a space can be translated in term of the amount of energy savings through a process of a building energy simulation. To get significant energy savings in general illumination, the electric lighting system must be incorporated with a daylight - activated dimmer control. A prototype configuration of an once interior has been established and the integration between the building envelope and lighting and HVAC systems is evaluated based on computer modeling of a lighting control facility. First of all, an energy-efficient luminaire system is designed and the lighting analysis program, Lumen-Micro 2000 predicts the optimal layout of a conventional fluorescent lighting future to meet the designed lighting level and calculates unit power density, which translates the demanded met of electric lighting energy. A dimming control system integrated with the contribution of daylighting has been applied to the operating of the artificial lighting. Annual cooling load due to lighting and the projecting saving amount of cooling load due to daylighting under overcast diffuse sky m evaluated by computer software ENER-Win. In brief, the results from building energy simulation with measured daylight illumination levels and the performance of lighting control system indicate that daylighting can save over 70 percent of the required energy for general illumination in the perimeter zones through the year A 25[%] of electric energy for cooling and almost all off heating energy may be saved by dimming and turning off the luminaires in the perimeter zones.

• Journal of KIISE
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• v.44 no.4
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• pp.417-422
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• 2017

Anomaly detection is the identification of data that do not conform to a normal pattern or behavior model in a dataset. It can be utilized for detecting errors among data generated by devices or user behavior change in a social network data set. In this study, we proposed a new approach using rank correlation coefficient to efficiently detect abnormal data in devices of a building. With the increased push for energy conservation, many energy efficiency solutions have been proposed over the years. HVAC (Heating, Ventilating and Air Conditioning) system monitors and manages thousands of sensors such as thermostats, air conditioners, and lighting in large buildings. Currently, operators use the building's HVAC system for controlling efficient energy consumption. By using the proposed approach, it is possible to observe changes of ranking relationship between the devices in HVAC system and identify abnormal behavior in social network.