• Journal of IKEEE
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• v.22 no.3
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• pp.672-679
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• 2018

Recently, microgrid (MG) has been proposed as one of the most critical solutions for various energy problems. For the optimal and economic operation of MGs, it is very important to forecast the load profile. However, it is not easy to predict the load accurately since the load in a MG is small and highly variable. In this paper, we propose an artificial neural network (ANN) based method to predict the energy use in campus buildings in short-term time series from one hour up to one week. The proposed method analyzes and extracts the features from the historical data of load and temperature to generate the prediction of future energy consumption in the building based on sparsified K-means. To evaluate the performance of the proposed approach, historical load data in hourly resolution collected from the campus buildings were used. The experimental results show that the proposed approach outperforms the conventional forecasting methods.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.337-344
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• 2012

Today, the number of super tall buildings are under construction or being planed in Middle East and Asian Countries. For example the burj Khalifa, the tallest building in the world, is completed in 2008 and the height of that is about 800m. Also, Lotte World Tower is under construction in Korea. External environmental conditions such as wind speed, air temperature, humidity and solar radiation around the super tall building differs according to the building height due to the vertical micro climate change. However, the meteorological information used for AC design of building is obtained typically from standard surface meterological station data(~2m above the ground). In this paper the effect of the building envelope on heating and cooling load in super tall building considering the meteorological changes with height was analyzed with simulation method. As results of this research, the guideline to select the building envelop alternatives for super tall building will be suggested in this paper.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.853-856
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• 2008

Windows have an great effect on annual building load because windows are the weakest parts of building envelope thermally. To reduce the consumption of building energy, the thermal performance of window has to be improved in first place. Therefore this research aims to make a quantitative analysis of the heating and cooling load according to the window thermal performance using the heat load simulation program. As a result of the simulation, annual heat load is down 38% according to the decrease of U-value of window, 1.00 W/$m^2K$. and annual heat load is up 10% according to the decrease of shading coefficient, 0.20. The annual load of the window with Low-E glass is 15% lower than the window with pair glass.

• Journal of the Korean Solar Energy Society
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• v.38 no.1
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• pp.1-11
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• 2018

In this work, we propose weather prediction models to estimate hourly outdoor temperatures and solar irradiance in the next day using forecasting information. Hourly weather data predicted by the proposed models are useful for setting system operating strategies for the next day. The outside temperature prediction model considers 3-hourly temperatures forecasted by Korea Meteorological Administration. Hourly data are obtained by a simple interpolation scheme. The solar irradiance prediction is achieved by constructing a dataset with the observed cloudiness and correspondent solar irradiance during the last two weeks and then by matching the forecasted cloud factor for the next day with the solar irradiance values in the dataset. To verify the usefulness of the weather prediction models in predicting a short-term building load, the predicted data are inputted to a TRNSYS building model, and results are compared with a reference case. Results show that the test case can meet the acceptance error level defined by the ASHRAE guideline showing 8.8% in CVRMSE in spite of some inaccurate predictions for hourly weather data.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.50 no.3
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• pp.292-300
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• 2014

The Laplace Transform solution is used as a mathematical model to analyse the thermal performance of the building constructed using different wall materials. The solution obtained from Laplace Transform is an analytical solution of an one dimensional, linear, partial differential equation for wall temperature profiles and room air temperatures. The main purpose of the study is showing the detail of obtaining solution process of the Laplace Transform. This study is conducted using weather data from two different locations in Korea: Seoul, Busan for both winter and summer conditions. A comparison is made for the cases of an on-off controller and a proportional controller. The weather data are processed to yield hourly average monthly values. Energy consumption load is well calculated from the solution. The result shows that there is an effect of mass on the thermal performance of heavily constructed house in mild weather conditions such as Busan. Building using proportional control experience a higher comfort level in a comparison of building using on-off control.

• KIEAE Journal
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• v.14 no.4
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• pp.47-52
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• 2014

The problem of energy consumption is more serious in university buildings than primary, middle and high school buildings. Because university buildings have generally heating and cooling systems, and various incidental facilities. In university, the library is one of the building that many people use and the most energy is spent. So, investigation on energy saving is very important and urgent. This study aims finally to present the guideline for low-energy design of University library by aiding a designer to select best solution in the side of energy-saving. In this paper, composition of space, utilization schedule and performance of construction materials are grasped, some primary factors that effect to energy saving are analyzed by energy simulation. The result of this study is as follows; First, the subject library has more cooling load than heating load because of cooling load generated during middle season. Second, green roofs is the most effective to heating load saving, but not to cooling energy. Third, outdoor air cooling is the most effective to cooling energy saving among the investigated strategies included in this study.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.05a
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• pp.193-195
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• 2011

Nowadays, climatic environment change has become a major issue in the world. This causes major emissions of carbon dioxide industries steel industry, thermal power industry, cement industry is essential in the reduction of carbon dioxide, which is based on total carbon dioxide emissions account for most of the construction industry in an effort to minimize the environmental load is needed. accordingly, through case studies, It can be induce the selection to minimize environmental load by comparing the output of quantitative energy consumption and carbon dioxide emissions per constructional methods. As a result of this study, RC Structure was less environmental load than SC structure.

• 한국태양에너지학회:학술대회논문집
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• 2011.11a
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• pp.196-201
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• 2011

The energy used in Korea is strongly dependent on that produced by foreign countries. Accordingly, saving energy is more important than ever, because of the rise of international oil prices and depletion of oil resources. The development of energy efficient buildings is required especially for public buildings in Korea. In this study, the energy use of public buildings is identify. Then, the analysis of energy usage through regional offices in Busan City offers energy performance for public buildings.

• KIEAE Journal
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• v.14 no.6
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• pp.105-110
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• 2014

The basic factors determining the amount of energy used in hospital buildings are weather conditions and building factors. But the real energy consumer is central plant equipment such as boilers and chillers that produce thermal energy for heating and cooling. Inaccurate decision of the primary equipment's size can cause a high initial-cost, an excessive equipment space, a wasted energy by low operation-efficiency and shortening of the machine's life. In this reason, the decision of optimal size for central plant equipment is very important. There are several factors for the decision such as an operation factor, a factor (equipment factor), piping losses and a simultaneous usage factor applied in the sizing process except a basic cooling load. But there is no standard method for applying those factors. Usually, factors are applied individually by an experience or custom of each engineer. In this study, the authors emphasize the meaning and the problem of those factors, examine them by analyzing factors which were applied to actual practices, and propose the recommendation value of safety, load, operation factors and application methods.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.9 no.1
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• pp.1-13
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• 1997

This paper reports the dynamic analysis of energy consumption for an office building by heat resistance-capacitance method. If a building is divided into several wall components and the wall components is replaced by one thermal capacitance and several thermal resistances, the building becomes an electric circuit. By solving the simultaneous equations of the circuit, the dynamic heat transfer characteristics and the energy consumption rate of the building were predicted. Accuracy of modified BIN method was evaluated by the present resistance-capacitance method. The result shows that modified BIN method overpredicts the heating load of the office building 15%. Annual energy consumptions of equipments(fan, boiler, chiller) for various ventilating control system(CAV, VAV, FCU+VAV, FCU+CAV) were compared. FCU+CAV shows the minimum annual energy consumption.