• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1276-1280
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• 2015

Among the various statistical factors for South Korea, the population has been steadily decreased by lower birthrate. Nevertheless, the number of household is constantly increasing amid population aging and single life style. In general, residential electricity use is more the result of the number of household than the population. Therefore, residential electricity consumption is expected to be far higher for decades to come. The existing long-term load forecasting, however, do not necessarily reflect the growth of single and two-member households. In this respect, this paper proposes the long-term load forecasting for residential users considering the effect of changes of the housing type, and in the case study the changes of the residential load pattern is analyzed for accurate long-term load forecasting.

• Journal of Industrial Technology
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• v.34
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• pp.61-66
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• 2014

Recently, Because the consumption of electricity is increased, having stable electricity supply and diagnosis of the power device is important. In this paper, I propose a diagnostic techniques of the leakage current for switchgear based on LabVIEW NI's. Using the data obtained from the leakage current sensor installed in switchgear panels, in performed continuously diagnosis, notifications and warnings can be the administrator immediately results. It is expected accordingly, the administrator will be able to take prompt action. Using the virtual switchgear with a PXI NI's, war tested the proposed techniques.

• Journal of Microbiology and Biotechnology
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• v.15 no.2
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• pp.281-286
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• 2005

We created a new graphite-Cu(II) electrode and found that the electrode could catalyze FADH$_2$ oxidation and FAD reduction coupled to electricity production and consumption, respectively. In a fuel cell with graphite-Cu(II) anode and graphite-Fe(III) cathode, the electricity was produced by coupling to the spontaneous oxidation of FADH$_2$ Fumarate and xylose were not produced from the enzymatic oxidation of succinate and xylitol without FAD, respectively, but produced with FAD. The production of fumarate and xylose in the reactor with FAD electrochemically regenerated was maximally 2- 5 times higher than that in the reactor with FAD. By using this new electrode with catalytic function, a bioelectrocatalysts can be engineered; namely, oxidoreductase (e.g., lactate dehydrogenase) and FAD can function for biotransformation without an electron mediator and second oxidoreductase for cofactors recycling.

• Progress in Superconductivity and Cryogenics
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• v.16 no.3
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• pp.10-14
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• 2014

Due to continuous increase of electric power consumption, couple of resolutions for improving accuracy in power system like line separation are being studied. The increase of the power demand can cause problems such as supply difficulties of the electricity and broadband outages, failure, etc. When a fault occurs in the power system, a fault current also increases. Fault current creates problems like reduction of lifespan and failure on the power system. In order to resolve these problems, the reduction of initial fault current using the characteristics of superconducting element was applied to fault current limiter. We applied the system to high speed fault current limiter. We found that the superconducting element effectively reduced initial fault current and the fault current was limited by changing operation of high speed interrupter.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.228-231
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• 2015

Recently, the electric power consumption concentrated in specific seasons and time causes the unstable power supply. To resolve this problem, smart grid has emerged as an alternative to consume the power, efficiently. Smart grid that combines ICT with the existing electrical grid includes demand response as a core technology. Demand response enable the power consumption effectively by offering a variety of informations, such as power consumption, charges expected, etc., for consumers who voluntarily participate in the electricity markets. In this paper, we design the automatic demand response systems based on SEP 2.0 for the efficient power control of home appliances in the smart grid environments.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.5
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• pp.376-383
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• 2022

The improved performance of computer parts, such as graphic card, CPU, and main board, has led to the need for power supplies with a high power output. The dynamic load profile rapidly changes the usage of power consumption depending on load operations, such as PC power and air conditioner. Under dynamic load profile conditions, power consumption can be classified into maximum, normal, and standby power. Several problems arise in the case of maximum power. Peak power is generated at the system power source in the maximum-power situation. Frequent generation of peak power can cause high-frequency problems and reduce the life of high-pressure parts (especially high-pressure capacitors). For example, when a plurality of PCs are used, system overload occurs due to peak power generation and causes problems, such as power failure and increase in electricity bills due to exceeded contract power. To solve this problem, a system peak power limit/compensation power circuit is proposed for a power supply under dynamic load profile conditions. The proposed circuit detects the system current to determine the power situation of the load. When the system current is higher than the set level, the circuit recognizes that the system current generates peak power and compensates for the load power through a converter using a super capacitor as the power source. Thus, the peak power of loads with a dynamic load profile is limited and compensated for, and problems, such as high-frequency issues, are solved. In addition, the life of high-pressure parts is increased.

• Journal of Satellite, Information and Communications
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• v.11 no.2
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• pp.42-47
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• 2016

Due to advances such as photovoltaic power generation and energy storage system, energy self-consumption smart home system in which energy management system is built and energy is generated in house has been actively researched. In particular, due to the instability of the grid after the Fukushima nuclear accident, home system in which generating electricity from photovoltaic, storing and using it in energy storage system was commercialized in Japan. While subsidizing renewable energy projects through a combination of solar and energy storage systems in North America and Europe has expanded home installation. In this paper, we describe development of self-consumption smart home system which is connecting photovoltaic system and energy storage system in home area network and operating it based on real-time price. We implemented automated self-consumption home in which optimizing the use of energy from the power grid with minimal user's intervention.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.2
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• pp.71-78
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• 2009

Up until recently, the energy and the economic analysis of a cogeneration system have been implemented by a manual calculation that is based on monthly thermal loads of buildings. In this study, a cogeneration system modeling validation with a detail building energy simulation, eQUEST, for a building energy and cost prediction has been implemented. By analyzing the hourly building electricity and thermal loads, it enables users to decide proper cogeneration system capacity and to estimate more accurate building energy consumption. eQUEST also verified the energy analysis when the heat pump system is integrated with the cogeneration system. The mechanical system configuration benefits from the high efficiency heat pump system while avoiding the building electricity demand increase. Economic analysis such as LCC (Life Cycle Cost) method is carried out to verify economical benefits of the system by applying actual utility rates of KEPCO(Korea Electricity Power COmpany) and KOGAS(KOrea GAS company).

• Journal of Advanced Technology Convergence
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• v.2 no.4
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• pp.43-48
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• 2023

Globally, there is a collaborative effort to achieve global carbon neutrality in response to climate change. In the case of South Korea, greenhouse gas emissions are rapidly increasing, presenting an urgent situation that requires resolution. In this context, this study developed a thermal energy collection device named a 'steam trap' and created an AI model capable of predicting future electricity usage by collecting energy usage data through steam traps. The average accuracy of electricity usage prediction with this AI model was 96.7%, demonstrating high precision. Consequently, the AI model enables the prediction and management of days with high electricity consumption and identifies which facilities contribute to elevated power usage. Future research aims to optimize energy consumption efficiency through efficient equipment operation using anomaly detection in steam traps and standardizing energy management systems, with the ultimate goal of reducing greenhouse gas emissions.

• Journal of IKEEE
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• v.25 no.2
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• pp.388-398
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• 2021

This paper proposes a particle swarm optimization (PSO)-based peak shaving scheme using energy storage system (ESS) for electricity tariff reduction. The proposed scheme compares the actual load with the estimated load consumption, calculates the additional output power that the ESS needs to discharge additionally to reduce peak load, and adds the input. In addition, in order to compensate for the additional power, the process of allocating power to the determined point is performed, and an optimization that minimizes the average of the load expected at the active power allocations using PSO so that the allocated value does not affect the peak load. To investigated the performance of the proposed scheme, case study of small and large load prediction errors was conducted by reflecting actual load data and load prediction algorithm. As a result, when the proposed scheme is performed with the ESS charge and discharge control to reduce electricity tariff, even when the load prediction error is large, the peak load is successfully reduced, and the peak load reduction effect of 17.8% and electricity tariff reduction effect of 6.02% is shown.