• Journal of Industrial Technology
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• v.31 no.A
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• pp.119-122
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• 2011

AWS (Automated Weather Station) wind data was used to predict the annual energy production of Gangwon wind farm having a total capacity of 98 MW in Korea. Two common wind energy prediction programs, WAsP and WindSim were used. Predictions were made for three consecutive years of 2007, 2008 and 2009 and the results were compared with the actual annual energy prediction presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm. The results from both prediction programs were close to the actual energy productions and the errors were within 10%.

• Korean Management Science Review
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• v.30 no.2
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• pp.1-10
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• 2013

Case studies are made to investigate the relationship between the accuracy of energy production estimation and project feasibility indicators such as rate of return on equity (ROE) and debt service coverage ratio (DSCR) for three wind farm projects. It is found out that 1% improvement in the accuracy of energy production estimation may enhance the ROE by more than 0.5% in the case of P95, thanks to improved financing terms. AHP survey shows that MCP correlation of measured in situ wind data with long term wind speed distribution and hands-on experiences of flow analysis are more important than other factors for more precise annual energy production estimation.

• Journal of the Korean Solar Energy Society
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• v.35 no.3
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• pp.1-8
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• 2015

The MERRA reanalysis data provided online by NASA was applied to predict the monthly energy productions of Donghai Bridge Offshore wind farms in China. WindPRO and WindSim that are commercial software for wind farm design and energy prediction were used. For topography and roughness map, the contour line data from SRTM combined with roughness information were made and used. Predictions were made for 11 months from July, 2010 to May, 2011, and the results were compared with the actual electricity energy production presented in the CDM(Clean Development Mechanism)monitoring report of the wind farm. The results from the prediction programs were close to the actual electricity energy productions and the errors were within 4%.

• Journal of the Korean Solar Energy Society
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• v.29 no.2
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• pp.22-30
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• 2009

In order to clarify predictive accuracy for the wind resource predicted by running WindPRO(Ver. 2.5) which is software for wind farm design developed by EMD from Denmark, an investigation was carried out at the northeast region of Jeju island. The Hangwon, Susan and Hoichun sites of Jeju island were selected for this study. The measurement period of wind at the sites was for one year. As a result, when the sites had different energy roses, though the two Wind Statistics made by STATGEN module were used for the prediction, it was difficult to exactly predict the energy rose at a given site. On the other hand, when the two Wind Statistics were used to predict the average wind speed, the wind power density and the annual energy production, the relative error was under ${\pm}20%$ which improved more than that when using only one Wind Statistics.

• Journal of the Korean Solar Energy Society
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• v.28 no.3
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• pp.45-52
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• 2008

In order to clarify characteristics of variation in wind energy over a long-term period, an investigation was carried out at Seoguang site on Jeju island. The wind data for 10 years from Automatic Weather System (AWS) were analyzed for each year. The variation in the annual energy production (AEP) for the 2 MW wind turbine was estimated through statistical work. The result shows that the range of the yearly average wind speed at 15 m above ground level for 10 years was from -22.6% to +13.7%, which is wider range than that in Japan. The coefficient of variation for the AEP was 22.7%, which is about twice of that for the yearly average wind speed. Therefore, for estimating the wind energy potential accurately at a given site, the wind data should be analyzed over a long-term period based on the data from the meteorological station.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.180.2-180.2
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• 2010

The purpose of this research is to analyze the sensitivity of WindSIM in complex terrain. As the flat areas for wind turbine installation become scarce globally, it becomes inevitable to install wind turbines in complex terrain. In order to predict annual energy production (AEP) in a more precise manner in complex terrain, it is of great importance to conduct such research. Three parameters: reference velocity, roughness and resolution have been chosen to see to which parameter WindSIM was the most sensitive in terms of annual energy production in complex terrain. By fixing two parameters and setting one parameter as a variable, it could be easily found that how annual energy production was effected by the change in each parameter.

• Journal of the Korean Solar Energy Society
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• v.29 no.4
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• pp.41-47
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• 2009

Wind/diesel hybrid operation can be one of the most effective option for electrical power production at a remote area such as Antarctica. The king Sejong station at Antarctica relies its power production on diesel engines and diesel oil is supplied every other year by ships. However, the oil transportation processes are liable to potential oil spillage caused by the floating ice around the King George island. The long-term storage of the oil at the station can also contaminate the surrounding soils. A l0kW wind turbine has been installed to save oil consumption and operated in connection with the diesel generators since 2006. The diesel engine that operated poorly during the first year of installation was replaced in 2008 to enhance power production an recent measurements indicate that both diesel power quality and the wind turbine availability have been dramatically improved by the replacement. This report discusses electrical power qualities of wind/diesel hybrid system operating at an isolated micro gird located in the king Sejong station. Our experience reveals that the similar technologies can be applied to domestic islands, for example, in the south sea.

• Journal of the Korean Solar Energy Society
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• v.31 no.2
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• pp.72-81
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• 2011

The wind data obtained from an AWS(Automated Weather Station) was used to predict the AEP(annual energy production) of Gangwon wind farm having a total capacity of 98 MWin Korea. A wind energy prediction program based on the Reynolds averaged Navier-Stokes equation was used. Predictions were made for three consecutive years starting from 2007 and the results were compared with the actual AEPs presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm. The results from the prediction program were close to the actual AEPs and the errors were within 7.8%.

• Journal of Power System Engineering
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• v.20 no.4
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• pp.44-51
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• 2016

An investigation on reliability of reanalysis wind data was conducted using the met mast wind data at four coastal regions, Jeju Island. Shinchang, Handong, Udo and Gangjeong sites were chosen for the met mast sites, and ERA-Interim and MERRA reanalysis data at two points on the sea around Jeju Island were analyzed for creating Wind Statistics of WindPRO software. Reliability of reanalysis wind data was assessed by comparing the statistics from the met mast wind data with those from Wind Statistics of WindPRO software. The relative error was calculated for annual average wind speed, wind power density and annual energy production. In addition, Weibull wind speed distribution and monthly energy production were analyzed in detail. As a result, ERA-Interim reanalysis data was more suitable for wind resource assessment than MERRA reanalysis data.

• Journal of the Korean Solar Energy Society
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• v.32 no.5
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• pp.94-101
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• 2012

A Dokdo wind resource map has been drawn up for the Green Island Energy Master Plan according to Korea's national vision for 'Low Carbon Green Growth'. The micro-siting software WindSim v5.1,which is based on Computational Flow Analysis, is used with MERRA reanalysis data as synoptic climatology input data, and sensitivity analysis on turbulence model is accompanied. A wind resource assessment has been conducted for the Dokdo wind power dissemination plan, which consists of two 10kW wind turbines to be installed at the Dongdo dock and Dokdo guard building. It is evaluated that the capacity factors at Dongdo dock and Dokdo guard building are about 20% and 30% respectively, and annual and hourly variations of wind power generation have been analyzed, but summertime energy production is predicted to be only 40% of wintertime energy production.