• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.5
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• pp.342-348
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• 2011

This study analyzes the current and after retrofit energy consumption of lighting and cooling system of a superstore in Seoul. Energy consumption data were measured and collected with a measurement system. Annual energy consumption was calculated using TRNSYS program. After replacing lighting and chiller with higher efficiencies, annual TOE consumption decreased from 1,066 before retrofit to 832 after retrofit, saving 234 TOE (22%) in total. Similarly, total annual $TCO_2$ consumption decreased from 2,214 to 1,721, reducing 493 $TCO_2$ (22%) during this pilot study.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.4
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• pp.329-337
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• 2015

In this paper, a simulation based estimation method of energy consumption of the spindle and feed drives for the NC machine tool during the cutting process is proposed. To predict energy consumption of the feed drive system, position, velocity, acceleration and jerk of the table are analyzed based on NC data and then the power and energy are calculated considering friction force and mass of the stages. Energy consumption of the spindle is estimated based on models from acceleration motion of rotating parts, friction torque and power loss of motors. Moreover, simulation models of cutting power and energy for the material removal along the NC tool paths are proposed.

• KIEAE Journal
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• v.12 no.2
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• pp.77-82
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• 2012

Data mining is to discover problems in the large amounts of data. Also, data mining trying to find the cause of the problem and the structure. Building energy consumption patterns, the amount of data is infinite. Also, the patterns have a lot of direct and indirect effects. Discussion is needed about the correlation. This work looking for the cause of energy consumption. As a result, energy management can find out the issue. Building energy analysis utilizing data mining techniques to predict energy consumption. And the results are as follows: 1) Using data mining technique, We classified complicated data to several patterns and gained meaningful informations from them. 2) Using cluster analysis, We classified building energy consumption data of residents and analyzed characters of patterns.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.506-510
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• 2012

This study suggested an improved algorithm of urban energy consumption estimation on the urban planning stage which concerns calculation accuracy. The results are as follows. (1) Urban energy consumption was estimated and managed per unit space using E-GIS DB which contains facility information per mesh. (2) Urban energy consumption was reflected by the urban facility classified and standardized by the characteristics of energy use. (3) Calculation accuracy of energy consumption was approached by separately suggested as summer algorithm reflecting urban heat island on summer energy use and winter algorithm reflecting heating system normally used in Korea.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.101-109
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• 2018

In this paper, we propose an adaptive filtering scheme of connection requests for the defense of malicious energy consumption attacks against wireless computing devices with limited energy budget. The energy consumption attack tries to consume the battery energy of a wireless device with repeated connection requests and shut down the wireless device by exhausting its energy budget. The proposed scheme blocks a connection request of the energy consumption attack in the middle, if the same connection request is repeated and its request result is failed continuously. In order to avoid the blocking of innocuous mistakes of normal users, the scheme gives another chance to allow connection request after a fixed blocking time. The scheme changes the blocking time adaptively by comparing the message arriving ate during non-blocking period and that during blocking period. Evaluation shows that the proposed defense scheme saves up to 94% energy consumption compared to the non-defense case.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.11a
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• pp.97-101
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• 2000

Energy consumption is considered as a principal ingredient in mobile wireless ad-hoc networks. In such a network, most of mobile nodes takes a role in forwarding messages received from neighbor nodes. Energy of these nodes is consumed in different rates depending on message traffic routes. This paper proposes a scheme to balance routing energy consumption by transferring routing function from node with small residual energy to node with enough residual energy. This scheme requires additional local message transfer, increasing the energy consumption of nodes to transfer routing function, and increasing total energy consumption of ad-hoc network. But balancing of energy consumption make the system lifetime the longer and increase the average node lifetime.

• Environmental Engineering Research
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• v.21 no.4
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• pp.409-419
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• 2016

As a major energy consumption province, the issue about the carbon emissions in Hebei Province, China has been concerned by the government. The carbon emissions can be effectively reduced due to a more rational energy consumption structure. Thus, in this paper the constraint of low carbon emissions is considered as a foundation and four energies--coal, petroleum, natural gas and electricity including wind power, nuclear power and hydro-power etc are selected as the main analysis objects of the adjustment of energy structure. This paper takes energy cost minimum and carbon trading cost minimum as the objective functions based on the economic growth, energy saving and emission reduction targets and constructs an optimization model of energy consumption structure. And empirical research about energy consumption structure optimization in 2015 and 2020 is carried out based on the energy consumption data in Hebei Province, China during the period 1995-2013, which indicates that the energy consumption in Hebei dominated by coal cannot be replaced in the next seven years, from 2014 to 2020, when the coal consumption proportion is still up to 85.93%. Finally, the corresponding policy suggestions are put forward, according to the results of the energy structure optimization in Hebei Province.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.8
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• pp.612-620
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• 2012

High economic growth causes increase of the building energy consumption. The energy consumption for HVAC system accounts for 40~50% of the whole building consumption. The trend for building is large-scale and high-rise. Because of the trend, the energy consumption is becoming bigger than before. Nowadays, HVAC system design are recognized as the solution for a energy-saving. This paper is focused on the energy performance evaluation of central air-conditioning system(water-based) and system air-conditioning that were applied to the office building. The systems are modeled and simulated by using EnergyPlus Software 6.0. After the Simulation, annual cooling and heating energy consumption were calculated. It was found that the system air-conditioning can reduce the energy consumption approximately 55.24% annually compared with the central air-conditioning system(water-cooled). In addition, about 46.13% of annual operating costs can be reduced by use of system air-conditioning.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.11
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• pp.605-611
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• 2017

The purpose of this study is to calculate the energy consumption rate based on data regarding energy use in office buildings, and to confirm the general characteristics of energy consumption. The energy consumption rate of the building is calculated by dividing the energy consumption by the floor area. The energy consumption rate of small-sized office buildings was calculated as $101.48{\sim}201.55kWh/m^2{\cdot}year$ and in the case of medium-sized buildings, the range was $92.77{\sim}177.89kWh/m^2{\cdot}year$. In the case of small buildings, it was found that the energy consumption was $73.24kWh/m^2{\cdot}year$ in electronic device, $34.31kWh/m^2{\cdot}year$ in hot water supply, and $18.37kWh/m^2{\cdot}year$ in heating. In the case of medium-sized buildings, electronic devices was $73.08kWh/m^2{\cdot}year$, lighting was $18.35kWh/m^2{\cdot}year$ and heating, $15.37kWh/m^2{\cdot}year$. In all of the study buildings, the peak heating energy use was observed from 8:00 a.m. to 10:00 a.m during the winter, and the peak power management was required. Energy use at and around the midnight hour is confirmed to be 40~60% of weekly working hours, so it is necessary to manage power use at night time as well as during the day. In order to improve the accuracy of future studies, it is necessary to make efforts to secure the data with standardized energy measuring units for the various type of buildings.

• Korean Journal of Construction Engineering and Management
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• v.16 no.3
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• pp.123-131
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• 2015

There are a number of policies that have been established to reduce greenhouse gases emissions and reduce energy consumption. These polices, however, only reflect the building energy consumption saving rate without considering building energy consumption characteristic. If building that already use less energy apply the same saving rate to reduce energy consumption, it is less effective. Therefore, this study classified building energy consumption characteristics and investigated approaches to adopt individual reduction rates according to energy consumption. Analysis results showed that there are differences in energy consumption depending on building use, and therefore, we classified buildings by use. We also proposed a formula to set a reduction goal for rate of energy consumption according to energy consumption. We verified our approach in a top-end neighborhood facility in Seoul. The energy consumption savings goal of this study can be applied individually, but determining whether a building can reduce energy consumption towards a saving goal requires a closer look at each building.