• Atmosphere
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• v.21 no.4
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• pp.439-446
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• 2011

NCEP reanalysis data were analyzed in order to provide distribution of global wind resource and wind speed in the surface layer for the years 2000-2009. Wind speed at 10 m above ground level (AGL) was converted to wind speed at 80 m above the ground level using the power law. The global average 80 m wind speed shows a maximum value of $13ms^{-1}$ at the storm track region. High wind speed over the land exists in Tibet, Mongolia, Central North America, South Africa, Australia, and Argentina. Wind speed over the ocean increased with a large value in the South China Sea, Southeast Asia, East Sea of the Korea. Sea surface wind in Western Europe and Scandinavia are suitable for wind farm with a value of $7-8ms^{-1}$. Areas with great potential for wind farm are also found in Eastern and Western coastal region of North America. Sea surface wind in Southern Hemisphere shows larger values in the high latitude of South America, South Africa and Australia. The distribution of low-resolution reanalysis data represents general potential areas for wind power and can be used to provide information for high-resolution wind resource mapping.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.393-405
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• 2023

Accurate prediction of wind speed and power is vital for enhancing the efficiency of wind energy systems. Numerous solutions have been implemented to date, demonstrating their potential to improve forecasting. Among these, deep learning is perceived as a revolutionary approach in the field. However, despite their effectiveness, the noise present in the collected data remains a significant challenge. This noise has the potential to diminish the performance of these algorithms, leading to inaccurate predictions. In response to this, this study explores a novel feature engineering approach. This approach involves altering the data input shape in both Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) and Autoregressive models for various forecasting horizons. The results reveal substantial enhancements in model resilience against noise resulting from step increases in data. The approach could achieve an impressive 83% accuracy in predicting unseen data up to the 24th steps. Furthermore, this method consistently provides high accuracy for short, mid, and long-term forecasts, outperforming the performance of individual models. These findings pave the way for further research on noise reduction strategies at different forecasting horizons through shape-wise feature engineering.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.518-528
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• 2022

Virtual Reality (VR) has been widely used in various applications to generate realistic virtual environments. A sense of immersion can be increased by providing additional stimuli such as tactile sensation to VR contents. However, it is still challenging to provide a realistic feel for the wind blowing over the whole body by smoothly controlling the airflow. To address this issue, we employ a household electric fan as a wind generating device to provide users with wind experience in VR environments. The wind generating device targets the whole body to mimic the wind we feel outside in our daily life. To do so, we present a low-cost method to smoothly control household fan speed using an Arduino microcontroller. Here, we use the Sinusoidal Pulse Width Modulation (SPWM) technique to generate the sinusoidal voltage required to drive the fan motor. Our experimental results show how Variable Voltage Variable Frequency (VVVF) is implemented at a low cost using our method for household fan speed control. The results can be applied to various VR applications to enhance the sense of immersion by providing users with realistic wind.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.14-17
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• 2005

Global latent heat flux data sets are crucial for many studies such as those related to air-sea interaction and climate variation. Currently, various global latent heat flux data sets are constructed using satellite data. Japanese Ocean Flux data sets with Use of Remote sensing Observations (J-OFURO) includes one of the satellite-derived global latent heat flux data (Kubota et aI., 2000). In this study, we review future development of J-OFURO global latent heat flux data set. In particular, we investigate usage of multi-satellite data for estimating accurate global latent heat flux. Accurate estimation of surface wind speeds over the global ocean is one of key factors for the improved estimation of global latent heat flux. First, we demonstrate improvement of daily wind speed estimation using multi-satellites data from microwave radiometers and scatterometers such as DMSP/SSMI, ERS/AMI, QuikSCAT/SeaWinds, AqualAMSR-E, ADEOS2/AMSR etc. Next, we demonstrate improvement of global latent heat flux estimation using the wind speed data derived from multi-satellite data.

• Journal of the Korean Solar Energy Society
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• v.30 no.4
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• pp.9-14
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• 2010

The main cause of global warming is carbon dioxide generated from the use of fossil fuels, and active research on the reduction of carbon is in progress to slow down the increasing global warming. Wind turbines generate electricity from kinetic energy of wind and are considered as representative for an energy source that helps to reduce carbon emission. Since the kinetic energy of wind is proportional to the cube of the wind speed, the intensity of wind affects wind farm construction validity the most. Therefore, to organize a wind farm, validity analysis should be conducted first through measurement of the wind resources. To facilitate the approval and permission and reduce installation cost, measuring sensors should be installed at locations below the actual wind turbine hub. Wind conditions change in shape with air density, and air density is most affected by the variable sterrain and surface type. So the magnitude of wind speed depends on the ground altitude. If wind conditions are measured at a location below the wind turbine hub, the wind speed has to be extrapolated to the hub height. This correction of wind speed according to height is done with the Deacon equation used in the statistical analysis of previously observed data. In this study, the optimal Deacon equation parameter was obtained through the analysis of the correction of the wind speed error with the Deacon equation based on the characteristics of terrain.

• New & Renewable Energy
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• v.10 no.2
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• pp.29-39
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• 2014

This study examines the future variability of surface wind speed and solar radiation based on climate change scenario over the Korean Peninsula. Climate change scenarios used in this study are RCP 4.5 and 8.5 with a 12.5 km horizontal resolution. Climate change scenario RCP 4.5 and 8.5 reproduce the general features of wind speed over the Korean Peninsula, such as strong wind speed during spring and winter and weak wind speed during summer. When compared with the values of wind speed and solar radiation of the future, they are expected to decrease current wind and solar resource map. Comparing the resource maps using RCP 4.5 and 8.5 scenarios, wind speed and solar radiation decrease with increasing greenhouse gas concentration. Meteorological resource maps of future wind and solar radiation should be improved with high resolution for the industrial application.

• Korean Journal of Applied Biomechanics
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• v.31 no.3
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• pp.162-167
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• 2021

Objective: This study aimed to identify the different wind speed categories and competitive level among windsurfers through GPS variables to provide the useful information on the development of training programs for enhancing windsurfers' performance. Method: Data from 69 female athletes who participated in 27 races during the 2018-2019 windsurfing season were used for the analysis. Average board speed, total race time, total distance, upwind race time, downwind race time, beam reach race time were collected through GPS. Unconfirmed data were excluded along with penalty point data. The wind conditions were classified as light, light to medium, medium, medium to heavy, and heavy wind, the competitive levels were classified as level 1, level 2, and level 3. Results: As for the average board speed, the level 1 or level 2 group showed higher board speed than the level 3 group in all wind conditions except for the light wind. The total race time and upwind race time showed less time in level 1 or level 2 group than level 3 group in all wind conditions. The total distance, downwind race time and beam reach race time showed less distance and time in level1 group than level 3 group under sufficient wind conditions. Conclusion: Our results show that the aerobic capacity to sustain pumping during upwind course in wind conditions below 15 kts effects performance. In wind conditions of 15 kts or more, indicated that the board control for the fast board speed and small distance required during up, down, beam reach courses had an effect on competition performance. This information can be provided to windsurfers and coaching as basic data for training programs to improve performance.

• Proceedings of the KSRS Conference
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• v.1
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• pp.146-149
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• 2006

Marine surface winds observed by two microwave sensors, SeaWinds and Advanced Microwave Scanning Radiometer (AMSR), on the Advanced Earth Observing Satellite-II (ADEOS-II) are evaluated by comparison with off-shore moored buoy observations. The wind speed and direction observed by SeaWinds are in good agreement with buoy data with root-mean-squared (rms) differences of approximately 1 m $s^{-1}$ and $20^{\circ}$, respectively. No systematic biases depending on wind speed or cross-track wind vector cell location are discernible. The effects of oceanographic and atmospheric environments on the scatterometry are negligible. The wind speed observed by AMSR also exhibited reasonable agreement with the buoy data in general with rms difference of 1.2 m $s^{-1}$. Systematic bias which was observed in earlier versions of the AMSR winds has been removed by algorithm refinements. Intercomparison of wind speeds globally observed by SeaWinds and AMSR on the same orbits also shows good agreements. Global wind speed histograms of the SeaWinds data and European Centre for Medium-range Weather Forecasts (ECMWF) analyses agree precisely with each other, while that of the AMSR wind shows slight deviation from them.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.286-291
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• 1998

SAR has provided weather independent images on land and sea surface, which can be used for extracting various useful informations. Recently attempts to estimate wind field parameters from SAR images over the oceans have been made by various groups over the world. Although scatterometer loaded in ERS-1 and ERS-2 observes the global wind vector field at spatial resolution of 50 Km with accuracies of $\pm$2m/s in speed, the spatial resolution may not be good enough for applications in coastal regions. It is weil known the sea surface roughness is closely correlated to the wind field, but the wind retrieval algorithms from SAR images are yet in developing stage. Since the radar backscattering properties of the SAR images are principally the same as that of scatterometer, some previous studies conducted by other groups report the success in mesoscale coastal wind field retrievals using ERS SAR images. We have tested SWA (SAR Wind Algorithm) and CMOD4 model for estimation of wind speed using an ERS-1 SAR image acquired near Cheju Island, Korea, in October 11, 1994. The precise estimation of sigma nought and the direction of wind are required for applying the CMOD4 model to estimate wind speed. The wind speed in the test sub-image is estimated to be about 10.5m/s, which relatively well agrees to the observed wind speed about 9.0m/s at Seoguipo station. The wind speed estimation through the SWA is slightly higher than that of CMOD4 model. The sea surface condition may be favorable to SWA on the specific date. Since the CMOD4 model requires either wind direction or wind speed to retrieve the wind field, we should estimate the wind speed first using other algorithm including SWA. So far, it is not conclusive if the SWA can be used to provide input wind speed data for CMOD4 model or not. Since it is only initial stage of implementing the wind field retrieval algorithms and no in-situ observed data is currently avaliable, we are not able to evaluate the accuracy of the results at the moment. Therefore verification studies should be followed in the future to extract reliable wind field information in the coastal region using ERS SAR images.

• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.67-77
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• 2022

The sense of touch by natural wind is one of the most common feels that every person experiences in daily life. However, it has been rarely studied how natural wind can be reproduced in a VR environment and whether the multisensory contents equipped with artificial winds do improve human emotion or not. To address these issues, we first propose a wind reproduction VR system guided by video and wind capture data and also study the effect of the system on positive affect. We collected wind direction and speed data together with a 360-degree video on a yacht. These pieces of data were used to produce a multisensory VR environment by our wind reproduction VR system. 19 college students participated in the experiments, where the Korean version of Positive and Negative Affect Schedule (K-PANAS) was introduced to measure their emotions. Through the K-PANAS, we found that 'inspired' and 'active' emotions increase significantly after experiencing the yacht VR contents with artificial wind. Our experimental results also show that another emotion, 'interested', is most notably affected depending on the presence of the wind. The presented system can be effectively used in various VR applications such as interactive media and experiential contents.