• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.2
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• pp.97-103
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• 2004

CHP system supplies electricity and heating together with high efficiency. Current utility's CHP system uses electric power by itself and sells thermal energy to KDHC(Korea District Heating Corporation). CHP's operation cost except sales revenue of heating was covered by the sale revenue of electricity. Thus Electric generation cost in district Heating CHP system has close relationship with the level of heating price. However, after the restructuring of electricity industry, the operation cost could not be covered by sales revenue of heating and electricity. This loss was compensated by energy subsidy program in the electric power industry infrastructure fund. This paper suggests reasonable evaluation and improvement methods of the loss calculation of CHP system utilizing the infrastructure fund efficiency In terms of the direction of support by the fund, it provides the methods to prevent inefficient operation through setting up the upper limit of subsidy and to improve the loss calculation. Moreover, it suggest fixed rate support by heating supply level and reducing subsidy gradually for an efficient operation of CHP system.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.30 no.1
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• pp.32-36
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• 2017

The Ag thin film of YBCO (yttrium barium copper oxide) CC (coated conductor) protect the YBCO layer and, at the same time, affects the electrical characteristics of the YBCO CC. Therefore, YBCO CC with the commercialization of the Ag thin film layers makes it easy to establish a process, it can lead to a variety of characteristic changes in YBCO CC. In this paper, plasma surface treatment was carried out to facilitate the deposition of the Ag thin film and the deposition process of YBCO CC. Surface roughness from the test results was increased as the time of the plasma surface treatment increased from 5 to 20 minutes. On the other hand, the surface roughness was decreased for the time of the plasma surface treatment over 20 minutes. Furthermore, after depositing, the increasing of deposit amount and reduced lifting phenomenon showed a similar tendency with the rise time of surface roughness.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.127-135
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• 2009

It is necessary to forecast the amount of the maximum electricity demand for stabilizing the flow of electricity. The time series data was collected from the Korea Energy Research between January 2000 and December 2006. The data showed that they had a strong linear trend and seasonal change. Winters seasonal model, ARMA model were used to examine it. Root mean squared prediction error and mean absolute percentage prediction error were a criteria to select the best model. In addition, a nonstationary generalized extreme value distribution with explanatory variables was fitted to forecast the maximum electricity.

• Nuclear Engineering and Technology
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• v.39 no.5
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• pp.655-662
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• 2007

Most decision makers in the electricity industry plan their electric power expansion program by considering only a least cost operation, even when circumstances change with differing complexities. It is necessary, however, to analyze a long-term power expansion plan from various points of view, such as environmental friendliness, benefit of a carbon reduction, and system reliability, as well as least cost operation. The objective and approach of this study is to analyze the proper role of nuclear power in a long-term expansion plan by comparing different scenarios in terms of the system cost changes, $CO_2$ emission reduction, and system reliability in relation to the Business-As-Usual (BAU). The conclusion of this paper makes it clear that the Korean government cannot but expand the nationwide nuclear power program, because an increased energy demand is inevitable and other energy resources will not provide an adequate solution from an economic and sustainability point of view. The results of this analysis will help the Korean government in its long-term resource planning of what kinds of role each electric resource can play in terms of a triangular dilemma involving economics, environmental friendliness, and a stable supply of electricity.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.969-977
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• 2021

We cluster the electricity consumption of households in A-apartment in Seoul, Korea using Hierarchical K-means clustering algorithm. The data is recorded from the advanced metering infrastructure (AMI), and we focus on the electricity consumption during evening weekdays in summer. Compare to the conventional clustering algorithms, Hierarchical K-means clustering algorithm is recently applied to the electricity usage data, and it can identify usage patterns while reducing dimension. We apply Hierarchical K-means algorithm to the AMI data, and compare the results based on the various clustering validity indexes. The results show that the electricity usage patterns are well-identified, and it is expected to be utilized as a major basis for future applications in various fields.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.89-100
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• 2021

Smart Grid Network (SGN) is a next generation electrical power network which digitizes the power distribution grid and achieves smart, efficient, safe and secure operations of the electricity. The backbone of the SGN is information communication technology that enables the SGN to get full control of network station monitoring and analysis. In any network where communication is involved security is essential. It has been observed from several recent incidents that an adversary causes an interruption to the operation of the networks which lead to the electricity theft. In order to reduce the number of electricity theft cases, companies need to develop preventive and protective methods to minimize the losses from this issue. In this paper, we have introduced a machine learning based SVM method that detects malicious nodes in a smart grid network. The algorithm collects data (electricity consumption/electric bill) from the nodes and compares it with previously obtained data. Support Vector Machine (SVM) classifies nodes into Normal or malicious nodes giving the statues of 1 for normal nodes and status of -1 for malicious -abnormal-nodes. Once the malicious nodes have been detected, we have done a trust evaluation based on the nodes history and recorded data. In the simulation, we have observed that our detection rate is almost 98% where the false alarm rate is only 2%. Moreover, a Trust value of 50 was achieved. As a future work, countermeasures based on the trust value will be developed to solve the problem remotely.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4506-4513
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• 2012

The purpose of this study is to analyze the causality of electricity consumption and econmic growth and draw policy implications. To do this, we used Testing Prodedures of Unit Root and Cointegration and then VECM and Granger causality test using data taken from China over the period 1971 to 2008. As results, there are long and short term causalities between electricity consumption and economic growth of China. These results provide a few implications to policy analysts in China. First it is still available that the electricity comes before the economic development. The increase of electricity consumption promotes economic growth. Of course there are other factors to the economic growth, but the stable supply of electricity is necessary. Second, this paper confirms the assertion that the increase of GDP expands electric consumption is valid.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.3
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• pp.391-395
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• 2016

In the last few decades, global electricity consumption has dramatically increased and has become drastically fluctuating and uncertain causing blackout. Due to the unexpected peak electricity demand, we need significant electricity supply. The solutions to these problems are smart grid system which is envisioned as future power system. Smart grid system can reduce electricity peak demand and induce effective electricity consumption through various price policies, demand response (DR) control methodologies, and state-of-the-art smart equipments in order to optimize electricity resource usage in an intelligent fashion. Demand response (DR) is one of the key technologies to enable smart grid. In this paper, we propose greedy technique for demand response smart grid system. The proposed scheme focuses on minimizing electricity bills, preventing system blackout and sacrificing user convenience.

• Environmental and Resource Economics Review
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• v.22 no.2
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• pp.251-279
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• 2013

Prices of oil products such as gasoline and diesel are deregulated since 1997 while electricity price is still controlled by government. This difference may explain recent discrepancy in the patterns of demand for oil products and electricity - constant increase in electricity consumption and stagnant demand for oil. To verify it empirically, we estimate price and income (production) elasticity of demand across time by using a rolling regression with 10 year-window based on monthly data for 1981-2011. Estimation results show that the sensitivity to price in demand for gasoline and diesel has increased since mid-90s while the elasticity of demand for electricity has become smaller. Second, income (production) elasticities of demand have shown no significant changes for both oil products and electricity. Third, cross-price elasticity was found meaningful only for gasoline before mid 1990s and for diesel after then.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.285-299
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• 2016

Although South Korea experienced a rolling blackout in 2011, the possibility of a blackout in South Korea continues to increase due to rapid electrification. This study examines the problems of energy taxation and price distortions as possible reasons for the rapid electrification in South Korea, which is occurring at a faster rate than in Japan, Europe, and other developed countries. Further, we suggest new energy taxation and price systems designed to normalize electricity prices. In order to do so, we consider two possible scenarios: the first imposes a tax on bituminous coal for electricity generation and the second levies a tax to provide compensation for the potential damages from a nuclear accident. Based on these scenarios, we analyze the effects of a new energy system on electricity price and demand. The results show that a new energy system could guarantee the power generation costs and balance the relative prices between energy sources, and could also help prevent rapid electrification. Therefore, the suggested new energy system is expected to be utilized as a basis for energy policy to decrease the speed of electrification, thus preventing a blackout, and to induce the rational consumption of energy in South Korea.