• 자원ㆍ환경경제연구
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• 제9권5호
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• pp.925-945
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• 2000

This paper analyses the impact of energy-saving investment on Greenhouse gas emissions using a model of energy demand in Korea. SUR method was employed to estimate the demand equation. The econometric estimates provide information about the energy price divisia index, sector income, and energy saving-investment elasticities of energy demand. Except for energy price divisia, the elasticities of each variable are statistically significant. Also, the price and substitution elasticities of each energy price are similar to the results reported by the previous studies. The energy-saving investment is statistically significant and elasticities of each sector is inelastic. Using the coefficient of energy-saving investment and carbon transmission coefficient, the amount of reduction of energy demand and the reduction of carbon emissions can be estimated. The simulation is performed with the scenario that the energy-saving investment increase by 10~50%, keeping up with Equipment Investment Plan of 30% increase in energy-saving investment by 2000. The results show that the reduction of energy demand measured as 11.2% based upon 1995's level of the energy demand, in industrial sector. Accordingly, the carbon emissions will be reduced by 11.3% based upon 1995's level of the carbon emissions in industrial sector.

• 자원ㆍ환경경제연구
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• 제11권4호
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• pp.525-556
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• 2002

This paper investigates effect of gasoline price liberalization on price elasticity of gasoline demand. By using a model where a consumer optimizes her gasoline consumption and number of visits to gas station, we derive price elasticity of gasoline demand and its response to variation of size and frequency in price changes. It shows that price elasticity is decreased with increase in the size and frequency when the price rises. Since price liberalization increases the frequency but reduces the size, the effect of the liberalization on the price elasticity may not be determined. However, price liberalization can make the elasticity higher when the size reduction effect exceeds the frequency increase effect, which is consistent with empirical evidence provided by existing studies.

• 한국입자에어로졸학회지
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• 제10권1호
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• pp.19-25
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• 2014

In line with the expected price reduction of natural gas associated with the introduction of shale gas, it is expected that the optimal power mix for the electric power generation be changed. In this study, the reconfigured power mix is estimated with the varying natural gas price by using the Screening Curve Method (SCM). It is found that about 3% and 9% coal in the overall power mix is replaced with natural gas if the natural gas price falls 20% and 40% of the current price, respectively. It is also found that the reconfigured power mixes would provide the reduction of the emissions of air pollutants which are equivalent to 369 and 807 MUS$.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.297-304
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• 2021

In a duopoly situation, one firm can gain competitive advantage by attracting the price-sensitive customers from its competitor leading to higher profits through higher sale revenue for the competing company. A simulation study in which there are two electric car manufacturers with agent based modelling was conducted in order to verify this contention. The first step consisted of defining the baseline. Simulations of 1000 times and agent-based modelling were conducted with the assumption that company 1 reduced its price to the maximum of 20% thereby contributing to the switch-over of a maximum of 40% of the price sensitive customers of company 2. The results of 1000 simulations and agent-based modelling highlighted that price reduction by company 1 resulted in a significant increase in the number of customers, presumably due to switch-over from company 2 and there was a corresponding increase in revenues from both of the sales avenues. Thus, Company 1 achieved competitive advantage by marketing its cars to the customers of Company 2 using price reduction strategy to attract them. This study has ramifications for companies that aim to sway the price sensitive customers from a competitor.

• 조명전기설비학회논문지
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• 제17권4호
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• pp.87-93
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• 2003

본 연구는 잠재가격을 사용하여 고조파를 효과적으로 저감시키는 새로운 방법을 제시한다. 우선, 고조파를 효과적으로 저감시키기 위하여 각 모선에 잠재가격을 적용하였으며, 전력수전점과 각 모선에서의 고조파한계치 이내로 고조파를 저감시킬 수 있는 새로운 알고리즘을 개발하였다. 그 결과, 배전계통에서 경제적으로 필터의 크기와 위치를 결정할 수 있도록 하였다. 제안한 방법을 실제계통에 적용하고, 그 유용성을 검증하였다.

• 자원ㆍ환경경제연구
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• 제23권4호
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• pp.617-641
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• 2014

2001년에 개설된 우리나라 전력도매시장은 변동비 반영(CBP) 시장으로 발전기들의 비용절감 유인을 통해 전력생산 비용 최소화를 추구하고 있다. 국내 발전사들은 발전비용 절감을 위한 다양한 노력을 기울여 왔고, 발전연료 구매비용의 인하, 고효율 발전기 도입, 수요지에 인접한 발전소 건설 등이 그 결과로 나타나고 있다. 최근 전력시장 제도개선의 일환으로 계통한계가격(SMP)에서 무부하비용 등을 제외하는 방식에 대한 논의가 제기되고 있다. 본 연구에서는 SMP에서 무부하비용 등을 제외한 후 손실발전기를 별도로 보상하는 방안이 발전사의 비용절감 유인에 미치는 영향을 분석하였다. 그 결과 가격결정 구간에 위치한 LNG복합 발전기들의 비용절감 유인이 위축될 가능성이 높은 것으로 나타났다.

• 전기학회논문지
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• 제67권4호
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• pp.512-521
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• 2018

Islands that is far away from onshore have used internal-combustion engine driving alternators to secure electric power. However, with Paris convention on climate change, there is a growing interest in eco-friendly energy independent island that replaces microgrid(MG) consisting of photovoltaic, wind power, and energy storage system with alternators for internal combustion engines. And also, national emission trading has been implemented, and the price of certified emission reduction(CER) has a influence on system marginal price(SMP). Because, the low cost generation source decides SMP when CER price is low, while the more expensive generation source decides SMP when CER price is high. Therefore, the increasing of CER price has a strong influence on the annualized return of MG independent power producer. Moreover, the fixed RPS price is implemented from 2017, which the increasing of CER price under the fixed RPS price or the variable RPS price affects annualized return differently. In this paper, the annualized return according to CER price is analyzed for large, middle, and small scaled islands, the effect of CER price on the annualized return was confirmed.

• 한국의류학회지
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• 제19권3호
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• pp.434-447
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• 1995

This research was intended to identify variables influencing on risk perception and risk reduction behavior in clothing purchase situations. Responses from 631 female adults living in Seoul area were collected and analyzed. Towner for social occasions or working in office was used as clothing stimulus. The analysis included three product variables(price, style, type of clothing), 4 personality variables(generalized self-confidence, specific self-confidence, generalized informativeness, fashion informativeness), 2 clothing attitude variables(clothing importance, clothing interest), 4 demographic variables(age, educational level, occupation, income), and 3 situational variables(purchase planning, time pressure, effects of shopping company). Multiple regression revealed the fact that each type of clothing risk and each type of risk reduction behavior was influenced by the set of different variables. Generalized self- confidence and age and time pressure had more effects on clothing risk perception, while clothing risk reduction behavior was more influenced by clothing risk type, clothing interest, price of clothing and fashion informativeness. Implications for marketing strategies planning were also provided.

• Communications for Statistical Applications and Methods
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• 제31권2호
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• pp.213-234
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• 2024

In recent decades, increasing research attention has been directed toward predicting the price of stocks in financial markets using deep learning methods. For instance, recurrent neural network (RNN) is known to be competitive for datasets with time-series data. Long short term memory (LSTM) further improves RNN by providing an alternative approach to the gradient loss problem. LSTM has its own advantage in predictive accuracy by retaining memory for a longer time. In this paper, we combine both supervised and unsupervised dimension reduction methods with LSTM to enhance the forecasting performance and refer to this as a dimension reduction based LSTM (DR-LSTM) approach. For a supervised dimension reduction method, we use methods such as sliced inverse regression (SIR), sparse SIR, and kernel SIR. Furthermore, principal component analysis (PCA), sparse PCA, and kernel PCA are used as unsupervised dimension reduction methods. Using datasets of real stock market index (S&P 500, STOXX Europe 600, and KOSPI), we present a comparative study on predictive accuracy between six DR-LSTM methods and time series modeling.

• 한국디지털건축인테리어학회논문집
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• 제12권1호
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• pp.89-98
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• 2012

While the housing transaction price of Seoul tends to be stagnant or declining in line with the housing market recession since 2007, the jeonse price keeps continual increase. Such flow of jeonse price change has a serious influence on ordinary person's housing stability seriously. Therefore, it is very meaningful in terms of social policy to analyze the trend of recent jeonse price change. This study aims to have an empirical analysis of structural characteristics of the trend of recent jeonse price change. After the review of various previous studies, this study selected housing jeonse price index, non-sold house quantity, jeonse vs. transaction price rate, and housing construction performance as analytical variables, and employed monthly time series resources from January 2007 to April 2011. As a result, when the housing supply reduced, the potential quantity for jeonse market reduced that occurred unbalance of supply and demand in jeonse market. In turn, it caused the increase of jeonse price. And, in case of jeonse vs. transaction price rate change, the rate increased which means the increase of required rate of return of invested demand. As such, the increase of market risk degenerates the investment sentiment which caused the reduction of quantity for jeonse market as a submarket.