• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2177-2186
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• 2017

The goal of this paper is to provide the specific forecasting steps and to explain how to design the forecasting architecture and training data sets to forecast very short-term wind power when the numerical weather prediction (NWP) is unavailable, and when the sampling periods of the wind power and training data are different. We forecast the very short-term wind power every 15 minutes starting two hours after receiving the most recent measurements up to 40 hours for a total of 38 hours, without using the NWP data but using the historical weather data. Generally, the NWP works as a predictor and can be converted to wind power forecasts through machine learning-based forecasting algorithms. Without the NWP, we can still build the predictor by shifting the historical weather data and apply the machine learning-based algorithms to the shifted weather data. In this process, the sampling intervals of the weather and wind power data are unified. To verify our approaches, we participated in the 2017 wind power forecasting competition held by the European Energy Market conference and ranked sixth. We have shown that the wind power can be accurately forecasted through the data shifting although the NWP is unavailable.

• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.351-362
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• 2012

Weather generators are statistical tools to produce synthetic sequences of daily weather variables. We propose the multisite weather generators with a spatio-temporal correlation based on hierarchical generalized linear models. We develop a computational algorithm to produce future weather variables that use three different types of green-house gases scenarios. We apply the proposed method to a daily time series of precipitation and average temperature for South Korea.

• Environmental and Resource Economics Review
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• v.15 no.2
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• pp.319-353
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• 2006

This paper shows how weather derivatives can be used to hedge against the price risk and volume risk of purchasing relatively large amounts of electricity. Our specific approach to designing new contracts for electricity is to focus on the return over a summer season rather than on the daily levels of demand and price. It is shown that correct market signals can be preserved in a contract and the associated financial risk can be offset by weather options. The advantage of combining a forward contract with a weather derivative is that the high prices on hot days or when the temperature is high reflect the underlying high cost of producing power when the load is high and that the combined contract with a weather derivative substantially reduces the volatility of the return.

• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.32.3-32.3
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• 2008

Solar and Space Weather Research Group in Korea Astronomy & Space Science Institute (KASI) has been funded for "Construction of Korean Space Weather Prediction Center" from Korean government. It has started since 2007 February and is planed as a 5-year project. The goal of this project is to develop a space weather warning and prediction system by the next solar maximum. KASI installed a magnetometer at Mt. Bohyun, which is about 200 km south-east apart from KASI, in 2007 September. After finishing test observations of the magnetometer for the period from September 2007 to January 2008, KASI has operated the magnetometer to monitor geomagnetic field variations associated with space weather effect. Ground-based magnetometers are critical for understanding geomagnetic disturbances in the near-Earth space environment, which are caused by solar wind variations. In this talk, we introduce science topics to be done with the data from KASI magnetometer and also discuss how they are related to space weather phenomena.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.6
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• pp.450-457
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• 2013

For the design guide of a vessel operating in cold region, numerical analysis was carried out to evaluate the weather-tight door which installed the heating cables by using ANSYS 13.0 Transient Thermal. The numerical analysis was performed by considering Advection-Diffusion equation. This study based on the experimental results of 'A study on Anti-Icing Technique for Weather-Tight Door of Ice-Strengthened Vessels'(Jeong, et al., 2011a) in KIOST. For validation of the numerical analysis results, the cold chamber experimental data measured by the heat sensors in certain location of the weather-tight door was used. The external environmental temperature which varies from $5^{\circ}C$ to $-55^{\circ}C$ was considered in numerical analysis. Also three different heating cables which have the heat capacity of 33W/m, 45W/m and 66W/m were adapted for the design parameters to be the most efficient and guidelines for anti-icing design of the weather tight door.

• The Journal of Bigdata
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• v.2 no.2
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• pp.129-140
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• 2017

Weather acts through low visibility, precipitation, high winds, and temperature extremes to affect driver capabilities, vehicle performance (i.e., traction, stability and maneuverability), pavement friction, roadway infrastructure, crash risk, traffic flow, and agency productivity. Recently a variety of road weather big data sources such as CCTV, road sensor/systems, car sensor have been developed to solve the weather-related problems, This study identifies and defines the types and characteristics of these sources to suggest how to utilize them for car safety and efficiency as well as road management through analyzing domestic and oversea cases of road weather big data applications.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.394-397
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• 2004

Working-day calculation with weather factors of construction-site has estimated wethout proper data. They usually estimate it with their own experience and intuition. It causes not only economic loss to time-adjustment but also conflict with each participants. Moreover, weather estimation becomes worse than before, due to tendency of recently weather change. So, in this paper we present optimal estimation method as assessment by period of the arithmetical mean methods. For that, we analyse characteristic of the regions and weather change of temperature and rainfall which affects time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.129-135
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• 2015

This study, in the operation of street lamp, suggests appropriate algorithm to extend the number of days of street lamp operation as much as possible if the number of sunless days continues and experimentally determines the value of Weather Factor necessary for this algorithm. This is conducted by reducing electricity consumption and securing battery remains through the use of standby power mode, in which maximum amount of light is maintained if there is a pedestrian, and constant brightness is maintained without utilizing maximum electric power if no pedestrians exist, with the application of WFactor value created by the algorithm considering weather forecast and amount of sunlight.

• Journal of Environmental Science International
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• v.20 no.3
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• pp.395-404
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• 2011

Weather forecasting is one of the key elements to improve health through the prevention and mitigation of health problems. Health forecasting is a potential resource creating enormous added value as it is effectively used for people. The purpose of this study is to estimate 'Willingness to Pay' for health forecasting. This survey was carried out to derive willingness to pay from 400 people who lived in Busan and Kyungnam Province and over 30 years of age during the period of July 1-31, 2009. The results showed that a 47.50% of people had intention to willingness to pay for health forecasting, and the pay was 7,184.21 won per year. Willing to pay goes higher depending on 'tax burden as to benefit of weather forecasting', 'importance of the weather forecasting in the aspect of health', 'satisfaction to the weather forecasting', and 'frequency of health weather index check'. This study followed the suggestion of the Korea Meteorological Administration generally and the values derived through surveys could be reliable. It can be concluded that a number of citizens who are willing to pay for health forecasting are high enough to meet the costs needed to provide health forecasting.

• Atmosphere
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• v.21 no.3
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• pp.285-300
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• 2011

To discriminate and eliminate chaff echoes in radar measurements, a new removal algorithm in two-dimensional reflectivity composite at the height of 1.5 km has been developed by using the brightness temperature($T_B$) obtained from MTSAT-1R. This algorithm utilizes the fact that chaffs are not appeared in infrared satellite data of MTSAT-1R, but detected in radar measurements due to their significant backscattering in the given radar wavelength. The algorithm is evaluated for three different situations: chaff only, chaff mixed with convective storms, and chaff covered with clouds. The algorithm shows excellent performance for the cases of chaff only and chaff mixed with convective storms. However, the performance of the algorithm significantly depends on the presence of clouds. Thus, the statistical analysis of $T_B$ is performed in order to optimize the monthly threshold.