• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.12
• /
• pp.1765-1773
• /
• 2012

The accuracy of load forecast is very important from the viewpoint of economical power system operation. In general, the weekdays' load demand pattern has the continuous time series characteristics. Therefore, the conventional methods expose stable performance for weekdays. In case of special days or weekends, the load demand pattern has the discontinuous time series characteristics, so forecasting error is relatively high. Especially, weekdays near the thanksgiving day and lunar new year's day have the mixed load profile characteristics of both weekdays and weekends. Therefore, it is difficult to forecast these days by using the existing algorithms. In this study, a new load forecasting method is proposed in order to enhance the accuracy of the forecast result considering the characteristics of weekdays and weekends. The proposed method was tested with these days during last decades, which shows that the suggested method considerably improves the accuracy of the load forecast results.

• Korean System Dynamics Review
• /
• v.7 no.2
• /
• pp.149-170
• /
• 2006

In this paper, an energy-economy-environment dynamic simulation model was developed to using system dynamics methodology. It describes current energy-economy-environment systems and forecasts changes caused by levying of carbon tax. The model is composed of three modules: an energy module, an economic module and an environmental module. Variables are interrelated in each module, and three modules are linked by several linkage variables. Setting up the linkage variables is an important factor for the composition of the model. The simulation result shows a change of the national GDP, usage of energy, and $CO_2$ emissions under levying and reinvestment of carbon tax considering various scenarios for the charging cost.

• Journal of the Korean Solar Energy Society
• /
• v.25 no.2
• /
• pp.9-17
• /
• 2005

Images taken by geostationary satellite may be used to estimate solar irradiance fluxes at earth's surface. It is based on the empirical correlation between a satellite derived cloud index and the irradiance at the ground. For the validation, estimated solar radiation fluxes are compared with observed solar radiation fluxes at 16 sites over the Korean peninsular from January 1982 to December 2004. Estimated solar radiation fluxes show reliable results for estimating the global radiation with average deviation of -7.8 to +7.0% from the measured values and the yearly averaged horizontal global insolation of Korean peninsula was turned out to be $3.56kW/m^{2}/day$.

• Solar Energy
• /
• v.20 no.3
• /
• pp.21-30
• /
• 2000

It is necessary to estimate the regression coefficients in order to predict the monthly mean daily global radiation on a horizontal surface. Therefore many different equations have proposed to evaluate them for certain areas. In this work, a new correlation has been made to predict the solar radiation for any area over Korea by estimating the regression coefficients taking into account percentage of possible sunshine, and cloud cover. Particularly, the multiple linear regression model proposed shows reliable results for estimating the global radiation with average deviation of -1 to 3 % from the measured values.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.32 no.5
• /
• pp.340-350
• /
• 2020

A rapid refresh wave forecasting system has been developed using the sea wind on the Korea Local Analysis and Prediction System. We carried out a numerical experiment for wind-wave interaction as an important parameter in determining the forecasting performance. The simulation results based on the seasons of with typhoon and without typhoon has been compared with the observation of the ocean data buoy to verify the forecasting performance. In case of without typhoon, there was an underestimate of overall forecasting tendency, and it confirmed that an increase in the wind-wave interaction parameter leads to a decrease in the underestimate tendency and root mean square error (RMSE). As a result of typhoon season by applying the experiment condition with minimum RMSE on without typhoon, the forecasting error has increased in comparison with the result without typhoon season. It means that the wave model has considered the influence of the wind forcing on a relatively weak period on without typhoon, therefore, it might be that the wave model has not sufficiently reflected the nonlinear effect and the wave energy dissipation due to the strong wind forcing.

• Publications of The Korean Astronomical Society
• /
• v.13 no.1 s.14
• /
• pp.39-54
• /
• 1998

We have developed solar observational system in the department of Astronomy & Space Sciences of KyungHee University, in order to monitor solar activities and construct solar database for space weather forecasting at maximum of 23rd solar cycle, as well as an solar education and exercise for undergraduate students. Our solar observational system consists of the full disk monitoring system and the regional observation system for H a fine structure. Full disk monitoring system is made of an energy rejection filter, 16cm refractor, video CCD camera and monitor. Monitored data are recorded to VHS video tape and analog output of video CCD can be captured as digital images by the computer with video graphic card. Another system for regional observation of the sun is made of energy rejection filter, 21cm Schmidt-Cassegrain reflector, H a filter with 1.6A pass band width and $375\times242$ CCD camera. We can observe H a fine structure in active regions of solar disk and solar limb, by using this system. We have carried out intense solar observations for a test of our system. It is found that Quality of our H a image is as good as that of solar images provided by Space Environmental Center. In this paper, we introduce the basic characteristics of the KyungHee Solar Observation System and result of our solar observations. We hope that our data should be used for space weather forecasting with domestic data of RRL(Radio Research Laboratory) and SOFT(SOlar Flare Telescope).

• Journal of Wind Energy
• /
• v.14 no.3
• /
• pp.25-33
• /
• 2023

In order to secure the safety of increasing offshore activities such as offshore wind farm maintenance and fishing, IMPACT, a mid-term marine weather forecasting system, was established by predicting marine weather up to 7 days in advance. Forecast data from the Korea Hydrographic and Oceanographic Agency (KHOA), which provides the most reliable marine meteorological service in Korea, was used, but wind speed and wave height forecast errors increased as the leading forecast period increased, so improvement of the accuracy of the model results was needed. The Model Output Statistics (MOS) method, a post-correction method using statistical machine learning, was applied to improve the prediction accuracy of wave height, which is an important factor in forecasting the risk of marine activities. Compared with the observed data, the wave height prediction results by the model before correction for 6 to 7 days ahead showed an RMSE of 0.692 m and R of 0.591, and there was a tendency to underestimate high waves. After correction with the MOS technique, RMSE was 0.554 m and R was 0.732, confirming that accuracy was significantly improved.

• Journal of Advanced Navigation Technology
• /
• v.21 no.6
• /
• pp.643-650
• /
• 2017

Photovoltaic generation which has unlimited energy sources are very intermittent because they depend on the weather. Therefore, it is necessary to get accurate generation prediction with reducing the uncertainty of photovoltaic generation and improvement of the economics. The Meteorological Agency predicts weather factors for three days, but doesn't predict the sunshine and solar radiation that are most correlated with the prediction of photovoltaic generation. In this study, we predict sunshine and solar radiation using weather, precipitation, wind direction, wind speed, humidity, and cloudiness which is forecasted for three days at Meteorological Agency. The photovoltaic generation forecasting model is proposed by using predicted solar radiation and sunshine. As a result, the proposed model showed better results in the error rate indexes such as MAE, RMSE, and MAPE than the model that predicts photovoltaic generation without radiation and sunshine. In addition, DNN showed a lower error rate index than using SVM, which is a type of machine learning.

• Journal of Korean Society for Atmospheric Environment
• /
• v.32 no.1
• /
• pp.32-45
• /
• 2016

The anthropogenic aerosols originated from the pollutant emissions in the eastern part of China and dust emitted in northwestern China in Yellow sand regions are subsequently transported via eastward wind to the Korean peninsula and then these aerosols induce high $PM_{10}$ concentrations in Korean peninsula. In order to estimate air quality considering anthropogenic and dust emissions, Comprehensive Air-quality Model with extension (CAMx) was applied to simulate $PM_{10}$ concentration. The predicted $PM_{10}$ concentrations without/with dust emissions were compared with observations at ambient air quality monitoring sites in China and Korea for 2008. The predicted $PM_{10}$ concentrations with dust emissions could depict the variation of measured $PM_{10}$ especially during Yellow sand events in Korea. The comparisons also showed that predicted $PM_{10}$ concentrations without dust emissions were under-predicted while predictions of $PM_{10}$ concentrations with dust emission were in good agreement with observations. This implied that dust emissions from desert and barren soil in southern Mongolia and northern China minimized the discrepancies in the $PM_{10}$ predictions in East Asia. The effect of dust emission on annual $PM_{10}$ concentrations in Korea Peninsula for year 2008 was $5{\sim}10{\mu}g/m^3$, which were about 20% of observed annual $PM_{10}$ concentrations.

• 한국신재생에너지학회:학술대회논문집
• /
• 2011.11a
• /
• pp.155-155
• /
• 2011

신재생에너지 수요가 확대됨에 따라 신재생에너지 관련 제품에 소요되는 물질에 대한 관심이 확대되고 있다. 이들 물질은 공급리스크가 존재하는 희유금속이 주를 이루고 있다. 본 연구에서는 신재생에너지 등의 high tech 기술 확대로 인한 희유금속의 수요 및 공급을 전망하고 있는 미국의 critical raw material 관리 전략을 살펴보고자 한다. 미국은 2010년 12월 미국 에너지성(DOE : Department of Energy)에서 위기 물질 전략(Critical Materials Strategy)에 관한 리포트를 공표하였다. 클린 에너지 기술 4개 분야(영구자석, 선진 전지, 태양전지 박막, 형광 물질)에서 핵심이 되는 물질(희유금속 등)의 수급 불균형이 일어날 가능성에 대해 조사를 실시하여 리스크 평가하여 단기, 중단기로 구분하여 위기물질을 선정하였다. 클린 에너지 기술 4개 분야에서 핵심이 되는 물질(네오디움, 디스프로슘, 코발트, 리튬, 랜턴, 세륨, 테룰, 인듐, 갈륨, 유로피움, 테르비움, 이트륨)의 12광종 수급을 2025년까지 전망한 결과 전체적으로 단기(2010년~2015년)보다 중기(2015년~2025년)에 공급 부족이 확대한다고 예측되었다. 단기적으로는 인듐이 약간 부족하는 것 외에 디스프로슘과 이트륨에 관해서도 공급 부족할 것으로 예측되었다. 중기적으로는 코발트(전지 기술에 사용)와 유로피움(고효율 조명용의 형광 물질에 사용) 외 대상이 된 다른 모든 물질은 공급 부족이 발생할 것으로 전망되었다. 이를 종합하여 단기적으로는 디스프리슘, 유로피움, 인듐, 테르븀, 네오디움, 이트륨 등이, 중기적으로는 디스프리슘, 유로피움, 테르븀, 네오디움, 이트륨 등이 위기물질(Critical Material)로 분석되었다. 에너지성은 위기물질을 공급원다각화, 대체물질개발, 리유즈, 리사이클링 등을 국제적 파트너와 함께 추진하여 리스크를 관리할 것이며, 2011년까지 최신정보를 구축하여 위기물질 전략을 재설정할 예정이다. 체계적인 위기물질 선정 및 관리전략 등을 참조하고, 신재생에너지기술 변화에 따른 원재료의 중요성 및 리스크 관리현황을 기초로 우리나라에 적합한 위기관리 물질 선정 및 관리가 필요할 것이다.