• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2626-2627
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• 1999

The device we have developed is the automatic shut off equipment which will reduce energy consumption when an equipment is in stand by power state. The principle for this system is when a man is moving, electricity will flow by setting a on-off light system. At night, in the stand-by power state the electric supply will be shut off immediately which will reduce energy consumption. Energy consumed by 24hour operating machines and stand-by electronic devices will be reduced by pulse signals which will give power supply when needed.

• Korean Journal of Construction Engineering and Management
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• v.14 no.4
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• pp.55-64
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• 2013

As GHG target management is introduced in Korea, designated establishment takes responsibilities to reduce more than 30% of expected GHG emission until 2020. Although decreasing GHG has been requested to universities which consume great amount of energy, there are difficulties to apply high cost countermeasures. Therefore, this research suggest a low cost, easily-applicable energy saving method, and derive potential GHG reduction amount in the case of SNU, Kwan-ak campus. First of all, 11 rooms of different use were chosen as the samples, and energy consumption in each room was measured. Standard models for each room were built through researching on the electric devices in each room. Moreover, energy consumption was computed for each devices through analyzing the pattern of electricity consumption. 32 GHG reduction technology and action program were chosen, and they were applied to the standard models for individual rooms. Through multiplying energy reduction rate of each program to energy consumption of each electric device, maximum energy reduction of each electric device is derived. Through that, Maximum GHG reduction for individual rooms and each month and the total GHG reduction capacity of Kwan-ak campus were computed. It was found out that approximately $5,311tCO_2$-eq can be reduced, when reduction technology and action program suggested by this research are applied. It appeared 24.48% of requested reduction amount to SNU can be reduced, till 2016.

• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.13-17
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• 2011

We have developed a new energy-consuming monitoring system that has made it possible to measure the energy consumption of a gas scrubber, one of semiconductor processing equipments, and installed this system to the gas scrubber under operating at a manufacture site. Using this system, we have measured consumptions of electric power and processing gas consumed at standby to operating mode. In case of the gas scrubber, processing gas flows continuously into it at standby and operating mode. Therefore, if the electric power has been supplied, the processing gas can flows into the device for 24 hours. Moreover, at operating of gas scrubber, the amount of electricity consumption is 5 kWh. At Standby of gas scrubber, it spends 3kwh. It is certain that the energy consumption is greater at operating mode than at standby mode. The carbon emission rates from 24 hour gas scrubber operation are 236 $kgCO_2$/day of $N_2$, 57 $kgCO_2$/day of electric power and 0.001 $kgCO_2$/day of cooling water. Most of carbon is emitted from $N_2$ gas and electric power consumption.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.7-14
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• 2021

The emergence of the automated smart grid has become an essential device for responding to these problems and is bringing progress toward a smart grid-based society. Smart grid is a new paradigm that enables two-way communication between electricity suppliers and consumers. Smart grids have emerged due to engineers' initiatives to make the power grid more stable, reliable, efficient and safe. Smart grids create opportunities for electricity consumers to play a greater role in electricity use and motivate them to use electricity wisely and efficiently. Therefore, this study focuses on power demand management through machine learning. In relation to demand forecasting using machine learning, various machine learning models are currently introduced and applied, and a systematic approach is required. In particular, the GP learning model has advantages over other learning models in terms of general consumption prediction and data visualization, but is strongly influenced by data independence when it comes to prediction of smart meter data.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.6
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• pp.27-34
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• 2001

There are several electricity applied sterilizers such as using high frequency, ozone, high voltage, and so on. Those sterilizers feature "because of no chemical process and no secondly environmental pollution". At the power conversion part, ZVS and ZCS methods have been used that it results in reduced switching loss, miniaturized size, and lightened weight. Besides, the current in the propose device is smaller than that of existing method. Thus, it is expected that the cost of sterilization process, when quality of the device is measured by power consumption, will be reduce. Therefore, the purpose of this research is to solve the sterilization problems of existing powder with high voltage and field to and more economical and effective way, and to suggest mere improved sterilizer.

• Journal of IKEEE
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• v.20 no.2
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• pp.163-166
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• 2016

It is important to operate the driving circuit under the optimal condition through precisely sensing the power consumption causing the temperature made mainly by the MOSFET (metal-oxide semiconductor field-effect transistor) when a BLDC (Brushless Direct Current) motor operates. In this letter, a Super-junction (SJ) power TMOSFET (trench metal-oxide semiconductor field-effect transistor) with an ultra-low specific on-resistance of $0.96m{\Omega}{\cdot}cm^2$ under the same break down voltage of 100 V is designed by using of the SILVACO TCAD 2D device simulator, Atlas, while the specific on-resistance of the traditional power MOSFET has tens of $m{\Omega}{\cdot}cm^2$, which makes the higher power consumption. The SPICE simulation for measuring the power distribution of 25 cells for a chip is carried out, in which a unit cell is a SJ Power TMOSFET with resistor arrays. In addition, the power consumption for each unit cell of SJ Power TMOSFET, considering the number, pattern and position of bonding, is computed and the power distribution for an ANSYS model is obtained, and the SJ Power TMOSFET is designed to make the power of the chip distributed uniformly to guarantee it's reliability.

• Journal of Internet of Things and Convergence
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• v.3 no.1
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• pp.25-31
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• 2017

In the future a future type new city and the latest apartment will be built, and the IoT technology will be constructed and combined in large numbers indoors of ordinary households. An air cleaner that makes people in it comfortable is built in, and the suction port that sucks in the air of the air purifier and the discharge port that discharges it are set up around the room and come out. However, this is impossible to adjust because there is only a central switch on / off. Also, consuming a lot of electricity so that many electricity charges are caused by huge electricity consumption will eventually be a waste of resources. This would like to be adjusted and driven through the fine dust detection device to the room built-in air purifier and that has provided a solution to save electricity. In addition, since it exists in and around the room, you can grasp the position of the person and connect to the home network to enhance the convenience. Also, through analysis of the air, we provide a health-check solution that checks the user's health and adjusts it appropriately.

• 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.

• Korean Chemical Engineering Research
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• v.55 no.6
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• pp.762-766
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• 2017

Energy recovery device (ERD) is used to save energy consumption in seawater reverse osmosis processes. However, small-scale ERDs (<$100m^3/d$) are hardly observed in seawater desalination market. In South Korea, most of seawater desalination plants for drinking water production are small-scaled and have been operated in island areas or on ships. Thus, the effect of ERDs for these small-scale SWRO processes should not be neglected. In this work, the small-scale SWRO processes are designed and analyzed in terms of energy consumption with/without ERD. The realistic efficiencies of high pressure pumps are considered for the energy analyses. The unit cost of electricity depending on the application place (e.g., inland and island areas, on ships) is investigated to calculate the energy cost for unit water production in various SWRO applications classified by plant capacity, application place, and the installation of ERD. As a result, the energy cost can be saved up to $1,640.4KRW/m^3$ when ERD is applied, and the saving effect increases at smaller plants on ships. In conclusion, the development of small-scale ERDs are necessary because small-scale SWRO processes are dominant in Korean seawater desalination market, and the electricity saving effect becomes higher at smaller-scaled system.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.155-156
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• 2015

Recently, electricity consumption has rapidly increased along with economic growth. The operating strategy using emergency generator is aimed, to resolve a demand response management. For strategy of peak shedding using emergency generator, it is essential to introduce the fast transfer switching device. One of the most effective solutions is to use a static transfer switch (STS) based on thyristor. However, the characteristic of natural commutated SCR thyristor should anticipate short duration voltage sag. STS system thus requires more than a quarter cycle to successfully complete transfer process. This paper proposes the operation scheme of the STS system using the forced-commutation technique to mitigate instantaneous voltage sag during peak transfer process. Proposed STS system improved turn-off characteristic thus accomplishes the peak load shedding satisfied power quality. Performance of the proposed STS system is evaluated using electromagnetic transient program (EMTP) to confirm the effectiveness.