• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.456-459
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• 2009

we studied a data acquisition and control system of a wind turbine for measuring and controlling a voltage fluctuations of a wind turbine system. The wind turbine system is installed out control area. So, it is so important for supervising to wind turbine of a maintenance, wind speed, optical resources wind turbine output, wind speed, wind direction, over voltage of a generator. This system can be supplied a data of over voltage, under voltage, voltage fluctuations of a wind turbine for controlling an EMS : Energy Management System or a SCADA : Supervision Control and Data Acquisition at a constitute of a wind farm. The of voltage fluctuation system of a wind turbine is improving an electric power supply power quality of a distribution line and unspecified individuals of used wind turbine.

• New & Renewable Energy
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• v.18 no.2
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• pp.18-25
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• 2022

In this study, we propose a wind power generation prediction system that applies machine learning and data mining to predict wind power generation. This system increases the utilization rate of new and renewable energy sources. For time-series data, the data set was established by measuring wind speed, wind generation, and environmental factors influencing the wind speed. The data set was pre-processed so that it could be applied appropriately to the model. The prediction system applied the CNN (Convolutional Neural Network) to the data mining process and then used the LSTM (Long Short-Term Memory) to learn and make predictions. The preciseness of the proposed system is verified by comparing the prediction data with the actual data, according to the presence or absence of data mining in the model of the prediction system.

• 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.

• Journal of the Korean Solar Energy Society
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• v.36 no.1
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• pp.49-61
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• 2016

The power production using hub height wind speed tends to be overestimated than actual power production. It is because the hub height wind speed cannot represent vertical wind shear and blade tip loss that aerodynamics characteristic on the wind turbine. The commercial CFD model WindSim is used to compare and analyze each power production. A classification of atmospheric stability is accomplished by Monin-Obukhov length. The concentric wind speed constantly represents low value than horizontal equivalent wind speed or hub height wind speed, and also relevant to power production. The difference between hub height wind speed and concentric equivalent wind speed is higher in nighttime than daytime. Under the strongly convective state, power production is lower than under the stable state, especially using the concentric equivalent wind speed. Using the concentric equivalent wind speed considering vertical wind shear and blade tip loss is well estimated to decide suitable area for constructing wind farm.

• Journal of the Korean Solar Energy Society
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• v.30 no.6
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• pp.66-72
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• 2010

In this study, we analyzed the characteristics of wind speed and wind direction at different locations in Jeju area using past 10 years observed data and used them in our wind power forecasting model. Generally the strongest hourly wind speeds were observed during daytime(13KST~15KST) whilst the strongest monthly wind speeds were measured during January and February. The analysis with regards to the available wind speeds for power generation gave percentages of 83%, 67%, 65% and 59% of wind speeds over 4m/s for the locations Gosan, Sungsan, Jeju site and Seogwipo site, respectively. Consequently the most favorable periods for power generation in Jeju area are in the winter season and generally during daytime. The predicted wind speed from the forecast model was in average lower(0.7m/s) than the observed wind speed and the correlation coefficient was decreasing with longer prediction times(0.84 for 1h, 0.77 for 12h, 0.72 for 24h and 0.67 for 48h). For the 12hour prediction horizon prediction errors were about 22~23%, increased gradually up to 25~29% for 48 hours predictions.

• Wind and Structures
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• v.18 no.2
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• pp.195-213
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• 2014

Recently, the horizontal axis rotor performance optimizer (HARP_Opt) tool was developed in the National Renewable Energy Laboratory, USA. This innovative tool is becoming more popular in the wind turbine industry and in the field of academic research. HARP_Optwas developed on the basis of two fundamental modules, namely, WT_Perf, a performance evaluator computer code using the blade element momentum theory; and a genetic algorithm module, which is used as an optimizer. A pattern search algorithm was more recently incorporated to enhance the optimization capability, especially the calculation time and consistency of the solutions. The blade optimization is an aspect that is highly dependent on experience and requires significant consideration on rotor control strategies, wind data, and generator type. In this study, the effects of rotor control strategies including fixed speed and fixed pitch, variable speed and fixed pitch, fixed speed and variable pitch, and variable speed and variable pitch algorithms on optimal blade shapes and rotor performance are investigated using optimized blade designs. The effects of environmental wind data and the objective functions used for optimization are also quantitatively evaluated using the HARP_Opt tool. Performance indices such as annual energy production, thrust, torque, and roof-flap moment forces are compared.

• Wind and Structures
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• v.9 no.6
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• pp.473-492
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• 2006

This paper presents numerical results of pedestrian-level wind environment around the base of a row of tall buildings by CFD. Four configurations of building arrangement are computed including a single square tall building. Computed results of pedestrian-level wind flow patterns and wind speeds are compared to previous wind tunnel measurement data to enable an assessment of CFD predictions. The CFD model uses the finite-volume method with RNG $k-{\varepsilon}$ model for turbulence closure. It is found that the numerical results can reproduce key features of pedestrian-level wind environment such as corner streams around corners of upwind building, sheltered zones behind buildings and channeled high-speed flow through a building gap. However, there are some differences between CFD results and wind tunnel data in the wind speed distribution and locations of highest wind speeds inside the corner streams. In locations of high ground-level wind speeds, CFD values match wind tunnel data within ${\pm}10%$.

• East Asian Journal of Business Economics (EAJBE)
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• v.3 no.3
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• pp.14-26
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• 2015

A wind speed forecast is a crucial and sophisticated task in a wind farm for planning turbines and corresponds to an estimate of the expected production of one or more wind turbines in the near future. By production is often meant available power for wind farm considered (with units KW or MW depending on both the wind speed and direction. Such forecasts can also be expressed in terms of energy, by integrating power production over each time interval. In this study, we technically focused on mathematical modeling of wind speed and direction forecast based on locally data set gathered from Aghdasiyeh station in Tehran. The methodology is set on using most common techniques derived from literature review. Hence we applied the most sophisticated forecasting methods to embed seasonality, trend, and irregular pattern for wind speed as an angular variables. Through this research, we carried out the most common techniques such as the Box and Jenkins family, VARMA, the component method, the Weibull function and the Fourier series. Finally, the best fit for each forecasting method validated statistically based on white noise properties and the final comparisons using residual standard errors and mean absolute deviation from real data.

• Wind and Structures
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• v.31 no.5
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• pp.419-430
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• 2020

Weibull distribution is a conspicuous distribution known for its accuracy and its usage for wind energy analysis. The two and three parameter Weibull distributions are adopted in this study to fit wind speed data. The daily mean wind speed data of Ennore, Tamil Nadu, India has been used to validate the procedure. The parameters are estimated using maximum likelihood method, least square method and moment method. Four statistical tests namely Root mean square error, R2 test, Kolmogorov-Smirnov test and Anderson-Darling test are employed to inspect the fitness of Weibull probability density functions. The value of shape factor, scale factor, wind speed and wind power are determined at a height of 100m using extrapolation of numerical equations. Also, the value of capacity factor is calculated mathematically. This study provides a way to evaluate feasible locations for wind energy assessment, which can be used at any windy site throughout the world.

• 한국태양에너지학회:학술대회논문집
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• 2011.04a
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• pp.213-216
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• 2011

The feasibility study must be conducted for construction of complex for generation of electric power such as items to get permission and grid connection etc. including wind resource to construct a complex for wind power generation. Since wind power can be used by converting only around 20~40% of energy coming in that kinetic energy of wind passes through blades and driving device into electric energy, when constructing a complex, the survey of wind resource takes up the most important part. Data logger used to measure this wind energy are expressed by calculating generally electromotive that is created from a sensor, variable-type, pulse-type signal to be proper for the actual value, and most data loggers have a type without considering geographical features. Besides, in the case of Met mast that is installed to survey the wind resource, since it is installed lower than the hub height of a wind power generator due to permission matters and the economic factors, the height of wind speed by utilizing Deacon equation is compensated to revise this. In this study, a device measuring wind speed was made by using algorithm that is possible to compensate the height of wind speed according to regional features and by applying Deacon equation, and the function of data storage through SD card or RS232 communication was added as well. Besides it's possible to check data more easily with a type of graph by using LCD touch screen for the convenience of users.