• Journal of the Korean Solar Energy Society
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• v.31 no.5
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• pp.119-125
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• 2011

In this paper, we have studied about minimizing the Energy Storage System (ESS) capacity for mitigating the fluctuation of Wind Turbine Generation System (WTGS) by using Electric Double Layer Capacitor (EDLC) and Battery Energy Storage System (BESS). In this case, they have some different characteristics: The EDLC has the ability of generating the output power at high frequency. Thus, it is able to reduce the fluctuation of WTGS in spite of high cost. The BESS, by using Li-Ion battery, takes the advantage of high energy density, however it is limited to use at low frequency response. To verify the effectiveness of the proposed method, simulations are carried out with the actual data of 2MW WTGS in case of worst fluctuation of WTGS is happened. By comparing simulation results, this method shows the excellent performance. Therefore, it is very useful for understanding and minimizing the ESS capacity for mitigating the fluctuation of WTGS.

• Journal of the Korean GEO-environmental Society
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• v.22 no.1
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• pp.5-12
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• 2021

Owing to economically efficient and easy installation, bucket foundation is a promising solution for offshore wind turbines. This paper aims at finding the behavior of suction caissons and soil surrounding the foundation by using three-dimensional finite element analysis. Under various loading conditions, a wide range of foundation geometries installed in dense and medium dense sandy soil was considered to evaluate ultimate horizontal load and overturning moment capacity. The results show that the rotation and displacement of the bucket due to monotonic loading are largely dependent on the foundation geometry, soil density and load eccentricity. Normalized diagrams and equations for the ultimate horizontal load and overturning moment capacities are presented that are useful tool for the preliminary design of such foundation type.

• Journal of Korea Port Economic Association
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• v.28 no.3
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• pp.27-44
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• 2012

The offshore wind farm is increasingly attractive as one of future energy sources all over the world. In addition, the capacity of an offshore wind turbine gets larger and its physical characteristics are big and heavy. In this regard, a special port is necessary to assemble, store, and transport the offshore wind systems, supporting to form the offshore wind farms. Thus, this study aims to provide a policy maker which evaluation factors can significantly affect to the optimal site selection of a offshore wind port. For this, Fuzzy-AHP method is applied to capture the relative weights. The results of this study can be summarized as follows. Five criteria in level I was defined such as the accumulation factor, the regional factor, the economic factor, the location factor, and the consortium factor. Of these, the accumulation factor(37.4%), the location factor(34.2%), and the economic factor( 24.5%) were analyzed by major factors. In level II, three assessment items of each factor were selected so that total fifteen items were formed. To sum up, the site selection of offshore wind port should consider the density of the wind industry, cargo volume of securing the economic operation of terminals, the development degree of offshore wind related industry, and the proximity to the offshore wind farms. In other words, the construction of offshore wind port should be paid attention to considering not only the proximity to offshore wind farms but also the preference of turbine manufacturing companies.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.963-969
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• 2021

The wind data measured from local meteorological masts is used to evaluate wind speed distribution and energy production in the specified site for wind farm However, wind data measured from meteorological masts often contain missing information or insufficient desired height or data length, making it difficult to perform wind turbine control and performance simulation. Therefore, long-term continuous wind data is very important to assess the annual energy production and the capacity factor for wind turbines or wind farms. In addition, if seasonal influences are distinct, such as on the Korean Peninsula, wind data with seasonal characteristics should be considered. This study presents methodologies for generating synthetic wind that take into account fluctuations in both wind speed and direction using the hidden Markov model, which is a statistical method. The wind data for statistical processing are measured at Maldo island in the Kokunnsan-gundo, Jeonbuk Province using the Automatic Weather System (AWS) of the Korea Meteorological Administration. The synthetic wind generated using the hidden Markov model will be validated by comparing statistical variables, wind energy density, seasonal mean speed, and prevailing wind direction with measurement data.