• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1103-1111
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• 2011

This paper is developed to Energy Balance Flow show the flow of total energy resource be used nationally. The Energy Balance Flow is applicable of demand management factor through the analysis of foreign energy model of supply and demand and energy statistic data in the country. This study is based on and developed to Energy system management model is able to appraisal efficient of energy cost cutting, CO2 emission reduction and Energy saving at the national level calculated effect reached amount of primary energy to change of energy flow followed application of demand side management factor is able to appraisal quantitatively at the total energy to model of demand and supply.

• Journal of Energy Engineering
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• v.25 no.2
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• pp.79-85
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• 2016

This paper presents an advanced energy demand management for buildings. It is important to aggregate a various demand side resource which is controllable on demand response environment. Previous demand side algorithm for building is mostly restricted on single building. In this paper, we suggest energy demand management algorithm for many buildings. And, this paper shows the procedure to apply suggested demand management algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1339-1346
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• 2011

This paper is developed to demand management scenario of energy consumption efficiency improvement, electricity generation efficiency improvement, network efficiency improvement, change of distribution ratio, movement of energy source, change of heating system, put of CHP to quantitatively assess to impact on energy use of demand management at the national level. This scenario can be applied Energy System Management model was developed based on Energy Balance Flow. In addition, effect analysis through built demand management scenario was quantitatively evaluated integrated demand management effectiveness of energy cost saving, CO2 emission reduction and energy savings of national level by calculating to primary energy source usage change in terms of integration demand management effect more often than not a single energy source separated electricity, heat and gas.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3307-3314
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• 2012

The annual energy demand of the standard rural house models was analyzed using the DesignBuilder. Indoor temperature set-point, U-value of outer wall, type of window, and degree of ventilation were selected as simulation parameters. In all the simulation cases, heating energy demand was higher than cooling energy demand regardless of the building size. When the lower U-value of the outer wall was applied to account for the thicker insulation layer, heating energy demand was decreased while cooling energy demand was increased. However, it is better to reduce the area of outer wall which is directly exposed to outdoor air because reducing the U-value of the outer wall is not effective in decreasing heating energy demand. Among the four different window types, the double skin window is most favorable because heating energy demand is the lowest. For a fixed infiltration rate, higher ventilation rate resulted in an increased heating energy demand and had minor impact on cooling energy demand. As long as the indoor air quality is acceptable, lower ventilation rate is favorable to reduce the annual energy demand.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.11
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• pp.636-642
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• 2009

Energy consumption data are surveyed and measured to develop energy demand models for hospital buildings as part of a complete package. Daily consumption profiles for electricity, heating, cooling and hot water are surveyed for 14 carefully chosen hospitals to establish energy demand patterns for a time span of a year. Then the hourly demand patterns of the 4 loads are field-measured for different seasons and statistically analyzed to provide higher resolution models. Used in conjunction with energy demand models for other types of buildings, the high resolution of 8760 hour energy demand models for a hospital for a typical year will serve as building blocks for the comprehensive model that allows the estimation of the combined loads for arbitrary mixtures of buildings.

• Journal of Energy Engineering
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• v.18 no.2
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• pp.114-124
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• 2009

The Ministry of Knowledge and Economy (MKE) establishes the Basic Plan for Long-Term Electricity Supply and Demand(BPE) biannually, a governmental plan for the stable electricity supply. This study investigated the effects of the electric demand forecast on the energy mix. A simplified simulation model was developed, which replaces the WASP program developed by the KPX and verified by comparing both results. Three different electric demand scenarios were devised based upon the 2005 electric demand forecast: Proper, 5 % higher, and 5% lower. The simplified model calculates the energy mix for each scenario of the year 2005. Then it calculates the energy mix for the proper electric demand forecast of the year 2007 using the energy mixes of the three scenarios as the initial conditions, so that it reveals the effect of electric demand forecast of the previous BPE on the energy mix of the next BPE. As the proper electric demand forecasts of the year 2005 and 2007 are the same, there is no change in the previous and the next BPEs. However when the electric demand forecasts were 5% higher in the previous BPE and proper in the next BPE, some of the planned power plant construction in the previous BPE had to be canceled. Similarly, when the electric demand forecasts were 5% lower in the previous BPE and proper in the next BPE, power plant construction should be urgently increased to meet the increased electric demand. As expected the LNG power plants were affected as their construction periods are shorter than coal fired or nuclear power plants. This study concludes that the electric demand forecast is very important and that it has the risk of long term energy mix.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.10
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• pp.553-558
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• 2009

Energy demand characteristics of hotel, hospital, and office building are compared to provide guidelines for combining building in community energy system design. The annual, monthly, and daily energy demand patterns for electricity, heating, hot water and cooling are qualitatively compared and important features are delineated based on the energy demand models. Key statistical values such as the mean, the maximum are also provided. Important features of the hourly demand patterns are summarized for weekdays and weekends. Substantial variations in both magnitudes and patterns are observed among the 3 building types and smart grouping or combination of building type and size is essential for a successive energy supply.

• Environmental and Resource Economics Review
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• v.9 no.5
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• pp.925-945
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• 2000

This paper analyses the impact of energy-saving investment on Greenhouse gas emissions using a model of energy demand in Korea. SUR method was employed to estimate the demand equation. The econometric estimates provide information about the energy price divisia index, sector income, and energy saving-investment elasticities of energy demand. Except for energy price divisia, the elasticities of each variable are statistically significant. Also, the price and substitution elasticities of each energy price are similar to the results reported by the previous studies. The energy-saving investment is statistically significant and elasticities of each sector is inelastic. Using the coefficient of energy-saving investment and carbon transmission coefficient, the amount of reduction of energy demand and the reduction of carbon emissions can be estimated. The simulation is performed with the scenario that the energy-saving investment increase by 10~50%, keeping up with Equipment Investment Plan of 30% increase in energy-saving investment by 2000. The results show that the reduction of energy demand measured as 11.2% based upon 1995's level of the energy demand, in industrial sector. Accordingly, the carbon emissions will be reduced by 11.3% based upon 1995's level of the carbon emissions in industrial sector.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1111-1115
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• 2014

With the increasing interest of a demand side management using a Smart Grid infrastructure, the demand resources and energy usage data management becomes an important factor in energy industry. In addition, with the help of Advanced Measuring Infrastructure(AMI), energy usage data becomes a Big Data System. Therefore, it becomes difficult to store and manage the demand resources big data using a traditional relational database management system. Furthermore, not many researches have been done to analyze the big energy data collected using AMI. In this paper, we are proposing a Hadoop based Big Data system to manage the demand resources energy data and we will also show how the demand side management systems can be used to improve energy efficiency.

• Journal of the Korean Solar Energy Society
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• v.39 no.5
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• pp.29-40
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• 2019

In response to the rapid climate change, in order to save energy in the field of buildings, the country is planning not only zero energy buildings but also zero energy cities. In the Urban Development Project, the Energy Use Plan Report is prepared and submitted by predicting the amount of energy demand at the planning stage. However, due to the activation of zero-energy buildings and the increase in the supply of new and renewable energy facilities, the energy consumption behavior of buildings in the city is changing from the previous ones. In this study, to estimate urban energy demand of Zero Energy City, building energy demand forecasts based on "Passive plans for use of energy based primary energy consumption", "Actual building energy usage data from Korea Appraisal Board" and "data from Certification of Building Energy Efficiency Rating" as well as demand forecast according to existing "Consultation about Energy Use Plan Code" were calculated and then applied to Multifunctional Administrative City 5-1 zone to compare urban total energy demand forecasts.