• Environmental and Resource Economics Review
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• v.25 no.2
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• pp.141-178
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• 2016

This paper, using AMR (Automatic Meter Reading) electricity data accurately measured in real time, analyses the characteristics and patterns of temperature effect on the industrial electricity usage. For this goal, the paper constructs and estimates a model which captures the properties of AMR time series including long-term trends, mid-term temperature effects, and short-term special day effects. Based on the estimated temperature response function and the temperature effect, we categorize the whole industry into two groups: one group with sharp temperature effect and the other with weak temperature effect. Furthermore, the industry group with sharp temperature effect is classified into a summer peak industry group and a winter peak industry group, based on the estimates of the temperature response function. These empirical results carry practical policy implications on the real time electricity demand management.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.810-811
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• 2007

기온의 변화에 따라 전력수요는 상관성을 가지고 밀접하게 움직이는데, 최근에 와서 상관성이 약화되는 경향을 보이면서 불확실성이 증가되고 있다. 이러한 현상이 나타나는 원인은 기온을 분포함수화하여 접근하지 못하고, 누적기온 영향력과 실질적 기온분포를 반영하지 못했기 때문이다. 따라서 이를 보완하기 위해 전력기온지수라는 개념을 새로 창출하였으며, 여기에 누적기온반응도, 유효기온분포 및 실질기온 효과를 반영하였다. 따라서 종합적 전력기상요인인 전력기온지수를 통해 전력소비자의 자발적 수요관리 유도 및 안정적 전력수급의 토대를 마련할 수 있다는 결론을 얻었다.

• Journal of Environmental Policy
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• v.13 no.2
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• pp.21-38
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• 2014

In response to global warming, the effect of the air temperature on water temperature has been noticed. The change in water temperature in river environment results in the change in water quality and ecosystem, especially Dissolved Oxygen (DO) level, and shifts in aquatic biota. Efforts need to be made to predict future water temperature in order to understand the timing of the projected river temperature. To do this, the data collected by the Ministry of Environment and the Korea Meteororlogical Administration has been used to build a nonlinear relationship between air and water temperature. The logistic function that includes four different parameters was selected as a working model and the parameters were optimized using SCE algorithm. Weekly average values were used to remove time scaling effect because the time scale affects maximum and minimum temperature and then river environment. Generally speaking nonlinear logistic model shows better performance in NSC and RMSE and nonlinear logistic function is recommendable to build a relationship between air and water temperature in Korea. The results will contribute to determine the future policy regarding water quality and ecosystem for the decision-driving organization.

• Environmental and Resource Economics Review
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• v.27 no.2
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• pp.287-313
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• 2018

This paper measures and analyzes cooling and heating demand in Korean electricity demand using time-varying temperature response functions and cooling and heating temperature effects. We fit the model to Korean data for residential and commercial sector over 1999:01~2016:12 and the estimation results show that the growth rate of heating demand is much higher than that of base and cooling demand, and especially the growth rate of heating demand in commercial sector is much higher. And we define the temperature-normalized demand conditioning that monthly temperatures are assumed as average monthly temperatures. The growth rate of heating demand in the estimated temperature-normalized demand is higher than that in the real demand. Our results are expected to be a base data for Winter Demand Management and short-term electricity demand forecasting.

• Environmental and Resource Economics Review
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• v.29 no.4
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• pp.419-442
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• 2020

The majority of the natural gas demand in South Korea is mainly determined by the heating demand. Accordingly, there is a distinct seasonality in which the gas demand increases in winter and decreases in summer. Moreover, the degree of sensitiveness to temperature on gas demand has changed over time. This study firstly introduces changing temperature response function (TRF) to capture effects of changing seasonality. The temperature effect (TE), estimated by integrating temperature response function with daily temperature density, represents for the amount of gas demand change due to variation of temperature distribution. Also, this study presents an innovative way in forecasting daily temperature density by employing functional principal component analysis based on daily max/min temperature forecasts for the five big cities in Korea. The forecast errors of the temperature density and gas demand are decreased by 50% and 80% respectively if we use the proposed forecasted density rather than the average daily temperature density.

• 한국지구과학회:학술대회논문집
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• 2010.04a
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• pp.80-80
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• 2010

본 연구에서는 식물의 개화시기가 기온에 민감하게 반응한다는 것에 근거하여 54개의 기상관측지점을 선택하고 1988년부터 2008년까지 21년간 벚꽃 개화일의 시계열적 변화를 분석하였고 이들과 3월 평균기온과의 상관관계를 조사하였다. 그리고 엘니뇨와 라니냐 시기에 기온과 벚꽃개화일의 변화 경향과 도시화에 의한 기온변화가 벚꽃 개화일에 미치는 영향을 대도시와 교외도시와의 비교를 통해 알아보았다. 또한 경험직교함수(EOF) 분석을 통하여 벚꽃개화일의 시 공간 분포를 알아보았다. 그 결과는 다음과 같다. 첫 번째, 3월 평균기온 분석을 통해 1988-2008년 사이에 한반도의 기온은 평균적으로 $0.13^{\circ}C$ 증가하였음을 확인할 수 있다. 그리고 평균적으로 남해안이 동해안과 서해안보다 평균기온이 높게 나타났으며, 서해안이 가장 낮은 평균기온을 보였다. 그리고 내륙지역의 경우 위도에 따라 평균기온이 달랐으며, 위도가 낮아질수록 평균기온이 크게 나타났다. 하지만 모든 지점에서 유의하지는 않았다. 두 번째, 벚꽃개화일의 변화를 보면, 개화일은 시간이 지날수록 빨라지는 경향을 보였다. 그리고 벚꽃개화일의 분포를 보면 위도가 낮은 지역이 개화일이 빨랐으며, 해안지역 중에서는 남해안, 동해안, 서해안 순이었다. 세 번째, 2월, 3월, 4월의 평균기온과 벚꽃 개화일의 상관관계 분석결과 3월 평균기온이 벚꽃개화일과 상관관계가 가장 높았다. 네 번째, 엘니뇨가 발생한 해에는 한반도의 기온이 상승하는 경향을 보였으며, 동시에 벚꽃개화일도 빨라졌다. 다섯 번째, 대도시가 교외도시에 비해서 기온상승이 높았으며, 벚꽃개화일도 빠르게 나타났다. 마지막으로, 경험직교함수(EOF) 분석 결과 3월 평균기온과 벚꽃 개화일의 1mode 시계열 패턴이 비슷하다는 것을 확인하였다. 또한, 1996년을 기준으로 이전에는 개화일이 느려지고, 이후에는 빨라지는 패턴을 보였다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.664-665
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• 2011

최근 겨울철과 여름철에 다양한 냉난방기기의 보급이 급증하여 최대전력에 대한 기온의 영향이 상당히 커지고 있다. 이에 따라 기온의 영향으로 인한 계절성이 급등하여 전력수요 예측결과의 불확실성을 증폭시키고 있다. 그러나 아직까지는 이러한 냉방 및 난방부하의 급증에 따른 계절성 변화에 대한 체계적인 분석 방법이 정형화되어 있지 못하다. 따라서 본 연구에서는 누적기온반응함수, 기온분포함수, 공적분 및 오차수정모형 등을 바탕으로 엄격한 통계적 검증을 거쳐 냉난방부하 추정 방법을 연구하였고, 아울러 관련 결과를 제시함으로써 향후의 전력수급에 안정적 기반을 제공코자 한다.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.3
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• pp.213-221
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• 2007

In response to anthropogenic global warming due to a buildup greenhouse gas, the effect of the air temperature on water temperature has been noticed and some efforts have been made to build an air/water temperature relationship at the Masan Bay area by the Ministry of Maritime Affairs & Fisheries (MOMAF). As a result of analyzing the auto- and cross-correlation coefficient between air/water temperature, high correlation $(\sim0.9)$ is shown and the correlation coefficient of air temperature is higher than that of water temperature at the lag time less than approximately 10 days. Separate functions are fitted to the air/water relationship at the Masan Bay to take hysteresis into account. The slopes of the straight line for the rising limb are 0.829 and 0.774 for MA1 and MA2 station respectively, while 1.385 and 1.444 ($\sim1.75$ times larger) for the falling limb. Consequently, the seasonal hysteresis should be considered in order to determine an air/water relationship and accurately estimate the water temperature using the air temperature at Masan Bay.

• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.703-720
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• 2019

The influence of temperature on electricity demand is increasing due to extreme weather and climate change, and the climate impacts involves nonlinearity, asymmetry and complexity. Considering changes in government energy policy and the development of the fourth industrial revolution, it is important to assess the climate effect more accurately for stable management of electricity supply and demand. This study aims to analyze the effect of temperature change on electricity demand using the partial linear model. The main results obtained using the time-unit high frequency data for meteorological variables and electricity consumption are as follows. Estimation results show that the relationship between temperature change and electricity demand involves complexity, nonlinearity and asymmetry, which reflects the nonlinear effect of extreme weather. The prediction accuracy of in-sample and out-of-sample electricity forecasting using the partial linear model evidences better predictive accuracy than the conventional model based on the heating and cooling degree days. Diebold-Mariano test confirms significance of the predictive accuracy of the partial linear model.

• The Korean Journal of Quaternary Research
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• v.13 no.1
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• pp.25-33
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• 1999

The relationships between climate (monthly precipitation and temperatures) and tree-ring growth of Korean fir (Abies koreana) growing at subalpine (1,600∼l,700m) zone on the south slope, Joong-Bong and the north slope, Changgun-Bong in the Cheonwang-bong area in Chiri mountains in the southern Korea were analyzed. Two cores from each of 10∼12 trees were extracted. The relationship between tree-ring(standardized) chronologies and climate was analyzed by the response-function method. Climate variables could explain 45.9∼53.8% of total variance in the chronologies. The precipitation response function of Korean fir were similar at both sites in overall ; positive for March∼May and August, and negative for February and July. The south-slope fir of Joong-Bong possessed higher negative temperature response function for February and August than north-slope one. The positive response function for April temperature was significant for both sites. In contrary to other subalpine species (e.g., Pinus koraiensis and Taxus cuspidata) in South Korea, whose growths are positively correlated with temperature in most seasons, the growths of Korean fir trees in Mt. Chiri appeared to be mainly limited by the moisture regime of spring prior to the cambial growth and early growing season.