• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.19 no.4
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• pp.8-17
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• 2023

The air temperature is gradually increasing owing to global warming, especially in summer, therefore, the performance of an air source heat pump (ASHP) is expected to be decreased. Accordingly, the performance gap between the ASHP and ground source heat pump (GSHP) should be increased, however, the quantitative comparison has not been yet investigated. In this study, impact of global warming on the performance of the ASHP and GSHP is investigated based on the climate data for 1930, 1980, and 2030. The coefficient of performance (COP) as well as annual power consumption of the ASHP and GSHP are compared and analyzed. In the case of COP, the COP of GSHP hardly changes over the years owing to the constant ground temperature, while that of ASHP decreases by 3.7% for cooling and increases by 0.71% for heating. In the case of annual power consumption, the cooling and heating power consumption of GSHP increases by 12.69% and decreases by 15.58%, respectively, over the year owing to the changes in heating and cooling loads. As for the ASHP, the cooling and heating power consumption increases by 16.64% and decreases by 17.8%, respectively. For a more accurate comparison, power consumption ratio is introduced and shows that total annual power consumption of the GSHP to ASHP decreased from 68% in 1930 to 65% in 2030. Therefore, as global warming accelerates, the effect of reducing power consumption by using GSHP compared to ASHP is expected to be increasing.

• The Journal of the Korea Contents Association
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• v.6 no.8
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• pp.1-7
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• 2006

In this paper, proposed the method to increase the battery life of the Wibro terminal by reducing its power consumption. The amount of power consumption was analysed. And as the results, it is shown that the suggested method can be reduced the power consumption. The performance of the proposed system, which control the number of pilot of symbol, analysed by the simulation. It is shown that the power consumption of the terminal can be reduced by the reduction of the CINR for the percentage of pilot per symbol, as 0.48dBm for 10% and 0.95dBm for 20%, which can be accomplished by changing the current system of having the fixed number of pilot.

• Journal of Power System Engineering
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• v.21 no.4
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• pp.84-93
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• 2017

This study was carried out to improve the electric power consumption of HVAC in the blow mold machine(BMM) and work environment. The experiment was conducted with the simulated HVAC system of 1/15 of the actual BMM. The temperature of main facility and two preheaters was fixed at 200 and $60^{\circ}C$ respectively in all test conditions. The measured points of temperature were chosen as critical locations considering the work environment. The tendency of temperature distributions decreases as the duct was closed to the main facility. The reduction rate of power consumption of HVAC increases up to 32.3% when both duct and cooling systems are operated. Also the efficiency of HVAC is improved about 9% through the modified design of duct system. It notes that the electric power consumption of HVAC can be reduced by the optimum design and operating condition of duct and cooling system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.6 s.360
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• pp.1-8
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• 2007

In wireless sensor network which uses limited battery, power consumption is very important factor for the survivality of the system. By using low-power communication to reduce power consumption, error rate is increased in typical conditions. This paper analyzes power consumption of specific error control coding (ECC) implementations. With identical link quality, ECC provides coding gain which save the power for transmission at the cost of computing power. In sensor node, transmit power is higher than computing power of Micro Controller Unit (MCU). In this paper, Viterbi algerian is applied to the low-transmit-power sensor networks in terms of network power consumption. Practically, Viterbi algorithm presents 20% of reduction of re-transmission in compared with Auto Repeat Request (ARQ) system. Furthermore, it is observed that network power consumption is decreased by almost 18%.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.307-316
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• 2009

In this paper, the spatiotemporal data mining methodology for detecting a cycle of power consumption pattern with the change of time and spatial was proposed, and applied to the power consumption data collected by GIS-AMR system with an aim to use its resulting knowledge in real world applications. First, partial clustering method was applied for cluster analysis concerned with the aim of customer's power consumption. Second, the patterns of customer's power consumption data which contain time and spatial attribute were detected by 3D cube mining method. Third, using the calendar pattern mining method for detection of cyclic patterns in the various time domains, the meanings and relationships of time attribute which is previously detected patterns were analyzed and predicted. For the evaluation of the proposed spatiotemporal data mining, we analyzed and predicted the power consumption patterns included the cycle of time and spatial feature from total 266,426 data of 3,256 customers with high power consumption from Jan. 2007 to Apr. 2007 supported by the GIS-AMR system in KEPRI. As a result of applying the proposed analysis methodology, cyclic patterns of each representative profiles of a group is identified on time and location.

• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.43-50
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• 2022

Correlation Power Analysis(CPA) is a sub-channel attack method that measures the detailed power consumption of attack target equipment equipped with cryptographic algorithms and guesses the secret key used in cryptographic algorithms with more than 90% probability. Since CPA performs analysis based on statistics, a large amount of data is necessarily required. Therefore, the CPA must measure power consumption for at least about 15 minutes for each attack. In this paper proposes a method of using a Convolutional Neural Network(CNN) capable of accumulating input data and predicting results to solve the data collection problem of CPA. By collecting and learning the power consumption of the target equipment in advance, entering any power consumption can immediately estimate the secret key, improving the computational speed and 96.7% of the secret key estimation accuracy.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.29 no.10
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• pp.630-634
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• 2016

In this paper, we analyzed the power consumption and the accumulated energy in HTSC (high-TC superconducting elements) according to the resistance of HTSC element and the winding current of transformer type SFCL (superconducting fault current limiter) using double quench. For the analysis, two different inductances of the one secondary winding among two secondary windings comprising the transformer type SFCL were selected and the short-circuit tests were carried out. The consumed power and the accumulated energy in HTSC element connected into the secondary winding with larger inductance were analyzed to be larger compared to the one connected into the secondary winding with lower inductance.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.81-94
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• 2022

This study sets the research goal of reducing energy consumption which 'H' University Industry-University Cooperation Foundation and resident companies are concerned with, as well as conducting policy research and data analysis. We tried to present a solution to the problem using the technique. The algorithm showing the greatest reliability in the power of the model for the analysis algorithm of this paper was selected, and the power consumption trend curves per minute and hour were confirmed through predictive analysis while applying the algorithm, as well as confirming the singularity of excessive energy consumption. Through an additional sub-sensor analysis, the singularity of energy consumption of the unit was identified more precisely in the facility rather than in the building unit. Through this, this paper presents a system building model for real-time monitoring of campus power usage, and expands the data center and model for implementation. Furthermore, by presenting the possibility of expanding the field through research on the integration of mobile applications and IoT hardware, this study will provide school authorities and resident companies with specific solutions necessary to continuously solve data-based field problems.

• Current Photovoltaic Research
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• v.11 no.4
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• pp.134-143
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• 2023

Efforts are being made to respond to global warming. Interest in and demand for the private sector-led RE100 campaign is also increasing. Self-built solar power generation, one of the implementation tools for RE100, is not expanding. However, it can be an economical means of implementation in the long run. In this study, we intend to analyze the impact on the optimal ratio of self-solar power generation using HOMER simulation. OPR defines the optimal solar power generation ratio and looks into what changes there are in the optimal solar power ratio when self-power consumption increases and external power purchase price changes. As a result, the optimal rate of self-solar power generation has a low impact even if self-power consumption increases. As the external power unit price increases, the optimal ratio increases, and at a power unit price of 100 KRW/kWh, OPR is 24%; at 200 KRW/kWh OPR is 31%; and at 300 KRW/kWh OPR is 34%. This shows that the electricity price replaced during the life cycle has a high impact on the economic feasibility of solar power generation. However, when the external power unit price reached a certain level, the increase in OPR decreased. This shows that it is difficult for domestic companies to achieve RE100 based on the economic feasibility of solar energy alone. Therefore, efforts are needed to supply renewable energy in the public sector.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.6
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• pp.85-90
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• 2014

This paper shows a reasonable demand power, that was made by the systematic and statistical way considering actual conditions, such as investigated transformer capacity and peak power for the last 6 years of subway substation customer as to AMR. In this dissertation, it is necessary to analyze the key features and general trend from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimum and thus it was carried by the linear and nonlinear regression analysis. And we studied on the application of a BESS. Analysis showed that the revulsion of capital is about 3 years and 4 months.