• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2676-2689
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• 2013

Due to increased consumption of energy in the building environment, the building energy management systems (BEMS) solution has been developed to achieve energy saving and efficiency. However, because of the shortage of building energy management specialists and incompatibility among the energy management systems of different vendors, the BEMS solution can only be applied to limited buildings individually. To solve these problems, we propose a building cluster based remote energy monitoring and management (EMM) system and its functionalities and roles of each sub-system to simultaneously manage the energy problems of several buildings. We also introduce a novel energy demand forecasting algorithm by using past energy consumption data. Extensive performance evaluation study shows that the proposed regression based energy demand forecasting model is well fitted to the actual energy consumption model, and it also outperforms the artificial neural network (ANN) based forecasting model.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.14 no.1
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• pp.16-21
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• 2018

This work aims to develop a platform to investigate the effect of operation schedules on the building energy consumption and to derive a simulation model based optimal start and stop daily strategy. An open-source building energy simulation tool DOE2 is used for the engine, and the developed simulation model is validated using ASHRAE guideline 14. The effect of late-start/early-stop operation of HVAC system on the daily building energy consumption was analyzed using the developed simulation model. It was found that about 10% of energy consumption cut was possible using the control strategy for an hour of advance of the stop operation, and about 3% per an hour of delay of the start operation.

• KIEAE Journal
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• v.13 no.3
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• pp.91-96
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• 2013

The purpose of this study was to analyze the annual energy demand including heating, cooling and lighting according to kind of windows with transparent thin-film a-Si Building Integrated Photovoltaic(a-Si BIPV) for office building. The analysis results of the annual energy demand indicated that the a-si BIPV window was reduced by 8.4% than the clear gazing window. The base model A was combinate with a-Si BIPV window area of 67% and clear window area of 33% among the total exterior area. The model B is to be applied with low-e clear glass instead of clear glass of the base model A. The model B was reduced to annual energy demand of 1% more than the model A. Therefore, By using a-si BIPV solar module, the cooling energy demand can be reduced by 53%(3.4MWh) and the heating energy demand can be increase by 58%(2.4MWh) than clear glazing window in office building. Also, Model C applied to the high efficient lighting device to the model B was reduced to annual energy demand of 14.4% more than the Model D applied to the high efficient lighting device to the model A. The Model E applied with daylight dimming control system to the Model C was reduced to annual energy demand of 5.9% more than Model C.

• Journal of the Korean Solar Energy Society
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• v.38 no.5
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• pp.75-84
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• 2018

The most crucial point of reducing building energy is application of high performance envelope. The amount of heat exchange through window is highest in comparison of other envelopes so that heat exchange through window influence directly with building energy consumption. The window energy performance can be define with thermal, leakage and optical performance. In previous study we can confirmed that not only thermal performance but also optical performance are considered, 11% to 15% of building energy consumption can be reduced. Smart window system has potential of energy saving so that many industry field use smart window system including architectural area and these aspect causes smart window market continuous growth year by year. In this study, building energy consumption has been analyzed which consist of smart window that dynamically control optical states. The consideration of standard commercial building model for research, the reference medium size commercial building model of DOE (Department Of Energy, USA) has been used. The building energy simulation result of 4 axis in 8 regions in Korea shows 8% to 22% reduction of building energy consumption by application of smart window system.

• KIEAE Journal
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• v.9 no.1
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• pp.107-113
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• 2009

The energy cost is resulted from the energy use. Its sources are divided into some types and depended on the building use or energy-use type. The energy cost should be affected by the amount of the energy use. The cost could be calculated to consider various factors such as the insulation, heating type, building shape and others. But it can not consider all of the affect factors to the energy cost and need to categorize the factors to the condition for estimating the cost. In this paper, it aimed at providing the estimation model in linear equation and multiple linear regression, utilizing the building exterior condition and management characteristics in apartment housing. Its survey are conducted in two parts of management characteristics and building exterior condition. The correlation analysis is conducted to get rid of the multicolinearity among the inputted factors. The number of linear equation model is 11 and includes the 1st, 2nd and 3rd equation function, power function and others. Among these, it suggested the 2nd and 3rd function and power function in terms of the statistics. In multiple linear regression model, the building volume and management area are inputted to the estimation.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.1
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• pp.9-15
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• 2009

There are various types of energy simulation tool to predict both thermal load and energy use. However, the problem about these software is that they have too much input variables and need expert with skills to run the simulation. Therefore, the purpose of this study is to develop the thermal analysis simulation program with input variables which eliminates coordinates of building components instead of using full coordinates by using DOE2. Since the simulation engine of the program is DOE2, the validity of S-DOE is performed by comparing peak heating and cooling load results with VisualDOE and annual energy use results with actual energy use of 1996. The results have shown that there are little difference between VisualDOE and S-DOE. Also it showed that there are little difference between actual energy use and S-DOE energy use results. S-DOE took less time to model a building than VisualDOE. These results reveals that the application of S-DOE have potentials in accurately predicting both energy load and energy use of the building and still have an advantage of taking less time to model a building.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.975-983
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• 2013

This study proposes a low order dynamic model of a building system in order to predict thermal behavior within a building and its energy consumption. The building system includes a thermally well-insulated room and an electric heater. It is modeled by a second order lumped RC thermal network based on the thermal-electrical analogy. In order to identify unknown parameters of the model, an experimental procedure is firstly detailed. Then, the different linear parametric models (ARMA, ARX, ARMAX, BJ, and OE models) are recalled. The parameters of the parametric models are obtained by the least square approach. The obtained parameters are interpreted to the parameters of the physically based model in accordance with their relationship. Afterwards, the obtained models are implemented in Matlab/Simulink(R) and are evaluated by the mean of the sum of absolute error (MAE) and the mean of the sum of square error (MSE) with the variable of indoor temperature of the room. Quantities of electrical energy and converted thermal energy are also compared. This study will permit a further study on Model Predictive Control adapting to the proposed model in order to reduce energy consumption of the building.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.8
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• pp.13-22
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• 2018

The purpose of this study was to consider the energy generation of the building as well as the energy demand of the building in terms of zero energy building design. The reason why the zero energy building viewpoint should be discussed is that direction of the building, heat transfer rate of the building, and the S/V ratio of the building are variables related to energy demand and solar panels installed on the building roof and building envelope are variables related to energy generation. This study proceeded as follows; Firstly, the simulation model of large office and elementary school has the same mutual volume and total floor area, and the each floor area and number of floors are adjusted so that the S/V ratio is different. To the next, the energy demand and energy generation of the simulation model were derived based on the meteorological data of Seoul, Daejeon, Busan. Finally, energy demand, energy generation, and final energy demand were compared with heat transfer rate, S/V ratio, building type, region, and orientation. The results of this study is that consideration of solar power generation in terms of energy generation should be taken into consideration at the same time in consideration of the heat transfer rate, the shape, the region and the direction of the zero energy building design.

• International Journal of Air-Conditioning and Refrigeration
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• v.14 no.3
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• pp.85-93
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• 2006

The present study has been conducted to simulate dynamics of a gas engine-driven heat pump (GHP) for the design of control algorithm. The dynamic model of a GHP was based on conservation laws of mass and energy. For the control of refrigerant pressures, actuators such as an engine throttle valve, outdoor fans, coolant three-way valves and liquid injection valves were controlled by P or PI algorithm. The simulation results were found to be realistic enough to be applied for the control algorithm design. The model could be applied to build a virtual real-time GHP system so that it interfaces with a real controller for the purpose of developing control algorithm.

• Advances in Energy Research
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• v.4 no.2
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• pp.107-120
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• 2016

The aim of this research is to apply the eQuest model to investigate the energy conservation in a multifamily building located in Dayton, Ohio by using a Trombe wall and an ammonia ground source heat pump (R-717 GSHP). Integration of the Trombe wall into the building is the first retrofitting measure in this study. Trombe wall as a passive solar system, has a simple structure which may reduce the heating demand of buildings significantly. Utilization of ground source heat pump is an effective approach where conventional air source heat pump doesn't have an efficient performance, especially in cold climates. Furthermore, the type of refrigerant in the heat pumps has a substantial effect on energy efficiency. Natural refrigerant, ammonia (R-717), which has a high performance and no negative impacts on the environment, could be the best choice for using in heat pumps. After implementing the eQUEST model in the said multifamily building, the total annual energy consumption with a conventional R-717 air-source-heat-pump (ASHP) system was estimated as the baseline model. The baseline model results were compared to those of the following scenarios: using R-717 GSHP, R410a GSHP and integration of the Trombe wall into the building. The Results specified that, compared to the baseline model, applying the R-717 GSHP and Trombe wall, led to 20% and 9% of energy conservation in the building, respectively. In addition, it was noticed that by using R-410a instead of R-717 in the GSHP, the energy demand increased by 14%.