• Atmosphere
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• v.16 no.3
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• pp.169-185
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• 2006

We have investigated the wind speed variations over the leeward region when the strong wind blows. In this study we employ Envi-met numerical model to simulate the effect of surface boundary conditions. This model is applied for three cases which are characterized by land use and terrain height. The base case having natural geographical condition shows the weakest wind speed around lee side of Chunsudae. The others which remove the vegetation and cut off the terrain above 20 m ASL represent the stronger wind speed than base case. The main factor of this result is the surface friction. The distinct variation of wind is found at offshore area between Chunsudae and the southern part of village, but the northern part where is apart from Chunsudae shows a small variation of wind pattern. The weakening of wind speed around residential area is a maximum of 4~10 m/s when the wind blows in the village as strong as 55 m/s. The gust wind speed is weakened about 7~17 m/s in this case if the coefficient of gust wind adapted as 1.75.

• Wind and Structures
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• v.37 no.2
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• pp.105-115
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• 2023

Structural design includes calculation of the wind speed as one of the major steps in the design process for wind loading. Accurate determination of design wind speed is vital in achieving safety that is consistent with the economy of construction. It is noticeable that many countries and regions such as Hong Kong, Japan and Australia regularly make amendments to improve the accuracy of wind load estimations for their wind codes and standards. This study compares the latest Hong Kong wind code published in 2019, which is generally known as the Code of Practice on Wind Effects in Hong Kong - 2019, with the latest revision of the AIJ Recommendations for Loads on Buildings - 2015 (Japan), and the Australian/New Zealand Standard, AS/NZS 1170.2:2021. The comparisons include the variations between the design wind speed and the vertical profiles of wind speed multipliers. The primary purpose of this study was to show any differences in the basic design wind speed and exposure factor estimations among the three economies located in the Western Pacific Ocean. Subsequently, the reasons for such underlying variations between the three documents, are discussed, together with future development trends.

• Journal of Wind Energy
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• v.15 no.2
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• pp.10-22
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• 2024

This research is a comprehensive analysis of wind power prediction sensitivity using a Long Short-Term Memory (LSTM) deep learning neural network model, accounting for the inherent uncertainties in wind speed estimation. Utilizing a year's worth of operational data from an operational wind farm, the study forecasts the power output of both individual wind turbines and the farm collectively. Predictions were made daily at intervals of 10 minutes and 1 hour over a span of three months. The model's forecast accuracy was evaluated by comparing the root mean square error (RMSE), normalized RMSE (NRMSE), and correlation coefficients with actual power output data. Moreover, the research investigated how inaccuracies in wind speed inputs affect the power prediction sensitivity of the model. By simulating wind speed errors within a normal distribution range of 1% to 15%, the study analyzed their influence on the accuracy of power predictions. This investigation provided insights into the required wind speed prediction error rate to achieve an 8% power prediction error threshold, meeting the incentive standards for forecasting systems in renewable energy generation.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.231-232
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• 2023

With taller buildings and larger typhoons, the impact of building winds is growing. During the 11th Typhoon Hinnamno in 2022, the building wind in Busan L City exceeded 60m/s, reaching the highest speed ever. Although many studies have been conducted on reducing the wind load of buildings, which is one of the problem factors caused by strong wind speed, there is a lack of research on wind speed reducing sculptures that can directly control strong wind speed. In this paper, several types of wind speed reduction sculptures were proposed to solve these problems, and the wind speed reduction capability of the proposed sculptures was analyzed through computational fluid dynamics (CFD). These results can contribute to suggesting effective design methods for improving the urban environment and reducing pedestrian stress.

• Wind and Structures
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• v.8 no.6
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• pp.389-406
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• 2005

The results of reference wind speed calculation in Croatia as a base for the revision of the Croatian standards for wind loads upon structures are presented. Wind speed averaged over 10 minutes, at 10 m height, in a flat, open terrain, with a 50-year mean return period is given for 27 meteorological stations in Croatia. It is shown that the greatest part of Croatia is covered with expected reference wind speeds up to 25 m/s. Exceptions are stations with specific anemometer location open to the bura wind which is accelerated due to the channelling effects of local orography and the nearby mountain passes where the expected reference wind speed ranges between 38 m/s and 55 m/s. The methodology for unifying all available information from wind measurements regardless of the averaging period is discussed by analysing wind speed variability at the meteorological station in Hvar.

• New & Renewable Energy
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• v.7 no.1
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• pp.15-21
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• 2011

In recent years, many countries have been endeavoring to exploit the offshore wind energy in terms of overcoming the limitations of on-land wind energy. Considering that mountains cover 70 percent of the Korean Peninsula and arable plains for wind energy are negligibly small, Korean government aggressively drives the offshore wind development of the Korean Peninsula. As part of preliminary investigation of offshore wind resources, KEPCO-RI (Korea Electric Power Corporation-Research Institute) has been analyzing marine buoy datasets measured at 5 positions over the period of 12 years, including estimation of extreme wind speed. It can be observed that variation of yearly wind speed, monthly wind speed as well as frequency distribution of wind direction. Wind classes of buoy sites are estimated by extrapolated average wind speed using log law. In addition, wind turbine class based on IEC code is assessed for evaluation of suitable wind turbine.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.92-99
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• 2016

A wind turbine is controlled for the purpose of obtaining the maximum power below its rated wind speed. Among the methods of obtaining the maximum power, TSR (Tip Speed Ratio) optimal control and P&O (Perturbation and Observation) control are widely used. The P&O control algorithm using the turbine power and rotational speed is simple, but its slow response is a weak point. Whereas TSR control's response is fast, it requires the precise wind speed. A method of measuring or estimating the wind speed is used to obtain a precise value. However, estimation methods are mostly used, because it is difficult to avoid the blade interference when measuring the wind speed near the blades. Neural networks and various numerical methods have been applied for estimating the wind speed, because it involves an inverse problem. However, estimating the wind speed is still a difficult problem, even with these methods. In this paper, a new method is introduced to estimate the wind speed in the wind-power graph by using the turbine power and rotational speed. Matlab/Simulink is used to confirm that the proposed method can estimate the wind speed properly to obtain the maximum power.

• Atmosphere
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• v.26 no.3
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• pp.461-471
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• 2016

A quality check algorithm for the Weather Information Service Engine pulsed Doppler wind lidar is developed from a view point of spatial and temporal consistencies of observed wind speed. Threshold values for quality check are determined by statistical analysis on the standard deviation of 3-component of wind speed obtained by a wind lidar, and the vertical gradient of horizontal wind speed obtained by a radiosonde system. The algorithm includes carrier-to-noise ratio (CNR) check, data availability check, and vertical gradient of horizontal wind speed check. That is, data sets whose CNR is less than -29 dB, data availability is less than 90%, or vertical gradient of horizontal wind speed is less than $-0.028s^{-1}$ or larger than $0.032s^{-1}$ are classified as 'doubtful', and flagged. The developed quality check algorithm is applied to data obtained at Bucheon station for the period from 1 to 30 September 2015. It is found that the number of 'doubtful' data shows maxima around 2000 m high, but the ratio of 'doubtful' to height-total data increases with increasing height due to atmospheric boundary height, cloud, or rainfall, etc. It is also found that the quality check by data availability is more effective than those by carrier to noise ratio or vertical gradient of horizontal wind speed to remove an erroneous noise data.

• New & Renewable Energy
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• v.17 no.4
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• pp.1-8
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• 2021

To determine the wind turbine class in the offshore of the Korean Peninsula, the reference wind speed for a 50-y return period at the hub height of a wind turbine was estimated using the reanalysis data sets. The most recent reanalysis data, ERA5, showed the highest correlation coefficient (R) of 0.82 with the wind speed measured by the Southwest offshore meteorological tower. However, most of the reanaysis data sets except CFSR underestimated the annual maximum wind speed. The gust factor of converting the 1 h-average into the 10 min-average wind speed was 1.03, which is the same as the WMO reference, using several meteorological towers and lidar measurements. Because the period, frequency, and path of typhoons invading the Korean Peninsula has been changing owing to the climate effect, significant differences occurred in the estimation of the extreme wind speed. Depending on the past data period and length, the extreme wind speed differed by more than 30% and the extreme wind speed decreased as the data period became longer. Finally, a reference wind speed map around the Korean Peninsula was drawn using the data of the last 10 years at the general hub-height of 100 m above the sea level.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.288-293
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• 2008

A predictive model of wind speed in the wind farm has very important meanings. This paper presents an estimation model of wind speed based on time series analysis using the observed wind data at Hangyeong Wind Farm in Jeju island, and verification of the predictive model. In case of Hangyeong Wind Farm and Haengwon Wind Farm, The ARIMA(Autoregressive Integrated Moving Average) predictive model was appropriate, and the wind speed estimation model was developed by means of parametric estimation using Maximum likelihood Estimation.