• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.8
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• pp.380-389
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• 2000

This paper presents a method for the regional long-term load forecasting in metropolitan area considering econimic indicator with the assumption that energy demands propoprtionally increases under the economic indicators. For the accurate load forecasting, it is very important to scrutinize the correlation among the regional electric power demands, economic indicator and other characteristics because load forecasting results may vary depending on many different factors such as electric power demands, gross products, social trend and so on. Three steps for the regional long-term load forecasting are microscopically and macroscopically used for the regional long -term load forecasting in order to increase the accuracy and practicality of the results.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.782-788
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• 2014

Wind power generation has been viewed as a promising renewable energy to meet challenge of climate change. However, wind power is susceptible to climate change because previous investigation shows there are declining trends of the land surface wind speeds over middle and lower latitudes. Since long term variation trends is notably different from inter-annual random variation and could have notable impact on wind farm from planning perspective, observed meteorological data of Taiwan is investigated to find out long term variation trends of wind speed and its impact on wind power generation. It is discovered that wind speed in majority of stations in west coast of Taiwan have ascending trends while that of all investigated stations in east coast have descending trends. Since east of Taiwan is not suitable for wind power development for its higher likelihood suffering Typhoons and most of established wind farm locate in west coast of Taiwan, it is speculated that long term variation trend of wind do not have notable negative impact on wind power generation in Taiwan.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.10
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• pp.389-398
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• 1985

Recently maximum power demand of our country has become to be under the great in fluence of electric cooling and air conditioning demand which are sensitive to weather conditions. This paper presents the technique and algorithm to forecast the long-term maximum power demand considering the characteristics of electric power and weather variable. By introducing a weather load model for forecasting long-term maximum power demand with the recent statistic data of power demand, annual maximum power demand is separated into two parts such as the base load component, affected little by weather, and the weather sensitive load component by means of multi-regression analysis method. And we derive the growth trend regression equations of above two components and their individual coefficients, the maximum power demand of each forecasting year can be forecasted with the sum of above two components. In this case we use the coincident dry bulb temperature as the weather variable at the occurence of one-day maximum power demand. As the growth trend regression equation we choose an exponential trend curve for the base load component, and real quadratic curve for the weather sensitive load component. The validity of the forecasting technique and algorithm proposed in this paper is proved by the case study for the present Korean power system.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.2
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• pp.109-115
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• 2016

The trend in appearance of storm waves on the east coast of Korea was investigated based on long-term wave data observed at six different stations. At the four wave stations of KIOST (Sokcho, Mukho, Hupo, and Jinha), no notable trend was found during the observation period with respect to the annual average and maximum values of the significant wave height. In addition, the annual number of the appearance of storm waves showed decreasing trend at the three stations except Jinha, where slightly increasing trend of the quantity was recognized. In contrast, at Donghea ocean data buoy of KMA, abruptly increasing trend was found for the annual average and maximum of the significant wave height and for the annual number of the appearance of storm waves as well, demonstrating lack of consistency in the observation data from Donghea buoy of KMA.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.23 no.2
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• pp.63-75
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• 2018

This study analyzed the long-term linear trends of the sea surface height around the Korea marginal seas for the period of 1993~2016 by using quantile regression. We found significant difference about 2~3 mm/year for the linear trend between OLS (ordinary least square) and median (50%) quantile regression especially in the Yellow Sea, which is affected by extreme events. Each area shows different trend for each quantile (lower (1%), median (50%) and upper (99%)). Most areas of the Yellow Sea show increasing trend in both low and upper quantile, but significant "upward divergence tendency". This implies that significant increasing trend of upper quantile is higher than that of lower quantile in this area. Meanwhile, South Sea of Korea generally shows "upward convergence tendency" representing that increasing trend of upper quantile is lower than that of lower quantile. This study also confirmed that these tendencies can be eliminated by removing major tidal components from the harmonic analysis. Therefore, it is assumed that the regional characteristics are related to the long term change of tide amplitude.

• Atmosphere
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• v.33 no.4
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• pp.355-365
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• 2023

To proactively manage climate risk, near-term climate predictions on annual to decadal time scales are of great interest to various communities. This study evaluates the near-term climate prediction skills in East Asia with DePreSys4 retrospective decadal predictions. The model is initialized every November from 1960 to 2020, consisting of 61 initializations with ten ensemble members. The prediction skill is quantitatively evaluated using the deterministic and probabilistic metrics, particularly for annual mean near-surface temperature, land precipitation, and sea level pressure. The near-term climate predictions for May~September and November~March averages over the five years are also assessed. DePreSys4 successfully predicts the annual mean and the five-year mean near-surface temperatures in East Asia, as the long-term trend sourced from external radiative forcing is well reproduced. However, land precipitation predictions are statistically significant only in very limited sporadic regions. The sea level pressure predictions also show statistically significant skills only over the ocean due to the failure of predicting a long-term trend over the land.

• Journal of Environmental Science International
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• v.11 no.11
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• pp.1141-1147
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• 2002

Based on the tide gauge data from the Permanent Service for Meau Sea Level (PSMSL) collected at 23 locations in the Korean coast, the long-term sea-level trend was computed using a simple linear regression fit over the recorded length of the monthly mean sea-level data. The computed sea-level trend was also corrected for the vertical land movement due to post glacial rebound(PGR) using the ICE-4G(VM2) model output. It was found that the PGR-corrected sea-level trend near Korea was 2.310 $\pm$ 2.220 mm/yr, which is higher than the global average at 1.0∼2.0mm/yr, as assessed by the Intergovernmental Panel on Climate Change(IPCC). The regional distribution of the long-term sea-level trend near Korea revealed that the South Sea had the largest sea-level rise followed by the West Sea and East Sea, respectively, supporting the results of the previous study by Seo et al. However, due to the relatively short record period and large spatial variability, the sea-level trend from the tide gauge data for the Korean coast could be biased with a steric sea-level rise by the global warming during the 20th century.

• Atmosphere
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• v.29 no.1
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• pp.13-20
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• 2019

Since 1985, the Dobson Spectrophotometer has been operated at Yonsei University, and this instrument has monitored the daily representative total ozone in Seoul. Climatological value for total ozone in Seoul is updated by using the daily representative observation data from 1985 to 2017. After updating the daily representative total ozone data, seasonal and inter-annual variation of total ozone in Seoul is also estimated after calculating inter-comparison between ground (Dobson Spectrophotometer) and satellite [Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI)] observations. The global average of total ozone measured by satellite is 297 DU, and its recent amount is about 3.5% lower than the global amount in 1980s. In Seoul, daily representative total ozone is ranged from 225 DU to 518 DU with longterm mean value of 324.3 DU. In addition, monthly mean total ozone is estimated from 290 DU (October) to 362 DU (March), and yearly average of total ozone have been continuously increased since 1985. For the long-term trend of total ozone in Seoul, this study is considered the seasonal variation, Solar Cycle, and Quasi-Biennial Oscillation. In addition to the natural oscillation effect, this study also considered to the long-term variation of sudden increase of total ozone due to the secondary ozone peak. By considering these natural effects, the long-term total ozone trends from 1985 to 2017 are estimated to be 1.11~1.46%/decade.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1581-1586
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• 2010

Korea Power Exchange has successfully performed the Long-term Electricity Demand Forecasting. Recently there is a lot of change in electricity industry sector; the national master-plan for green gas emission reducing, rise of smart-grid, and new trend of electricity consumption, and it is becoming painful challenging for demand forecasting. In new circumstance the demand forecasting is required more flexible and more accurate.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.1
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• pp.101-119
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• 2018

In this study, we analyzed long-term measurements and air quality simulation results of four criteria air pollutants ($PM_{10}$, $O_3$, $NO_2$, and $SO_2$) for 10 years, from 2006 to 2015, with emphasis on trends of annual variabilities. With the observation data, we conducted spatial interpolation using the Kriging method to estimate spatial distribution of pollutant concentrations. We also performed air quality simulations using the CMAQ model to consider the nonlinearity of the secondary air pollutants such as $O_3$ and the influence of long-range transport. In addition, these simulations are used to deduce the effect of long-term meteorological variations on trends of air quality changes because we fixed the emissions inventory while changing meteorological inputs. The nation-wide inter-annual variability of modeled $PM_{10}$ concentrations was $-0.11{\mu}g/m^3/yr$, while that of observed concentrations was $-0.84{\mu}g/m^3/yr$. For the Seoul Metropolitan Area, the inter-annual variability of observed $PM_{10}$ concentrations was $-1.64{\mu}g/m^3/yr$ that is two times rapid improvement compared to other regions. On the other hand, the inter-annual variability of observed $O_3$ concentrations is 0.62 ppb/yr which is larger than the simulated result of 0.13 ppb/yr. Magnitudes of differences between the modeled and observed inter-annual variabilities indicated that decreasing trend of $PM_{10}$ and increasing trend of $O_3$ are more influenced by emissions and oxidation states than meteorological conditions. We also found similar patterns in $NO_2$. However, $NO_2$ trends showed greater regional and seasonal differences than other pollutants. The analytic approach used in this study can be applicable to estimate changes in factors determining air quality such as emissions, weather, and surrounding conditions over a long term. Then analysis results can be used as important data for air quality management planning and evaluation of the chronic impact of air quality.