A long-term wind resource map was made to provide the key design data for the 2.5 GW Korean West-South Offshore Wind Project, and its reliability was validated. A one-way dynamic downscaling of the MERRA reanalysis meteorological data of the Yeongwang-Gochang offshore was carried out using WindSim, a Computational Fluid Dynamics based wind resource mapping software, to establish a 33-year time series wind resource map of 100 m x 100 m spatial resolution and 1-hour interval temporal resolution from 1979 to 2012. The simulated wind resource map was validated by comparison with wind measurement data from the HeMOSU offshore meteorological tower, the Wangdeungdo Island meteorological tower, and the Gochang transmission tower on the nearby coastline, and the uncertainty due to long-term variability was analyzed. The long-term variability of the wind power was investigated in inter-annual, monthly, and daily units while the short-term variability was examined as the pattern of the coefficient of variation in hourly units. The results showed that the inter-annual variability had a maximum wind index variance of 22.3% while the short-term variability, i.e., the annual standard deviation of the hourly average wind power, was 0.041±0.001, indicating steady variability.

Three meteor-statistical forecasting models - the transfer function model, the time-series autoregressive model and the neural networks model - were tested to develop a daily forecasting model for Jejudo, where the need and demand for wind power forecasting has increased. All the meteorological observation sites in Jejudo have been classified into 6 groups using a cluster analysis. Four pairs of observation sites among them, all having strong wind speed correlation within the same meteorological group, were chosen for a model test. In the development of the wind speed forecasting model for Jejudo, it was confirmed that not only the use a wind dataset at the objective site itself, but the introduction of another wind dataset at the nearest site having a strong wind speed correlation within the same group, would enhance the goodness to fit of the forecasting. A transfer function model and a neural network model were also confirmed to offer reliable predictions, with the similar goodness to fit level.

Recently, wind power generation is an emerging industry expanding its market rapidly thanks to the increasing need to solve the scarcity of fossil fuels and the risk of potential global warming. Wind power generation has shown to be an effective response plan to global warming, showing the most price competitiveness among the renewable energy sources by its higher efficiency. Therefore wind energy has attracted considerable attention as the industrial growth drive for the next generation. Considering Korea’s high dependence of overseas energy resources, the importance of wind power is growing as the most effective alternative energy source to ensure energy security as well as becoming a key strategic industry for exports. In this study, the social and economic effects of the wind power industry is discussed and the current status and the future prospects of the wind energy market is also examined.

The physical properties of an atmospheric boundary layer in Wolryong, a west coastal region of Jeju, South Korea, in terms of the atmospheric stability and roughness length, is important and relevant to both engineers and scientists. The study is aiming to understand the atmospheric stability around this region and its effect on the roughness length. We calculate the Monin-Obukhov length(L) against 3 typical regions of the atmospheric condition - unstable regime (-5<H/L<-0.2), neutral regime (-0.2≤H/L≤0.2) and stable regime (0.2<H/L<2), where H is the measurement height. The diurnal Monin-Obukhov length substantially varies in the night, but most of the H/L comes under the neutral regime. The roughness length scale can be derived by three different methods - logarithmic profile, standard deviation and gust factor method. The finding in the study is that the methods of the standard deviation and the gust factor, apart from the logarithmic profile, are all similar in terms of the roughness length under the different atmospheric conditions. In addition, they have sufficiently shown the effect of obstacles and surface conditions around the measurement site.

In order to support the development of wind farms in Jejudo, a wind resource database for Jejudo has been established using a meteor-statistical analysis of KIER(Korea Institute of Energy Research) met-mast measurements and KMA(Korea Meteorological Administration) weather data. The analysis included wind statistics, tower shading, an exposure category classification using satellite images, the effect of atmospheric stability on the wind profile exponent, and a correlation matrix of wind speed to gain an understanding of the meteorological correlation between long-term weather observation stations and short-term met-mast measurements. The wind resource database for Jejudo, is to be provided as an add-on to Google EarthTM, which is expected to be utilized as a guideline for the selection of an appropriate reference site for long-term correction in the next wind farm development project.