• Journal of Korean Society of Coastal and Ocean Engineers
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• v.27 no.5
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• pp.281-294
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• 2015

In order to quantitatively estimate the nonlinear destructive interaction of wave load with wind load, which is very vital for the optimal design of offshore wind energy converter, we carried out a hydraulic model test and wind tunnel test. As a substructure of offshore wind energy converter, we would deploy the monopile, which is popular due to its easiness in construction. Based on the simulation using Monte Carlo simulation using Kaimal spectrum and cross spectrum, the instantaneous maximum wind velocity is adjusted to 10 m/s. And, considering the wave conditions of the Western Sea where a pilot wind farm is planned to be constructed, $H_s=0.1m$, 0.15 m, 0.2 m is carefully chosen. It turns out that the nonlinear destructive interaction between the wind and wave loads acting on the offshore wind energy converter is more clearly visible at rough seas rather than at mild seas, which strongly support our deduction that a Large eddy, a swirling vortex developed near the bumpy water surface in the opposite direction of the wind, is the driving mechanism underlying nonlinear destructive interaction between the wind and wave loads.

• Journal of IKEEE
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• v.23 no.1
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• pp.173-180
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• 2019

There is a case where the output of renewable energy(RE) is curtailed due to an increase in the share of RE. Typically, wind power(WP) is curtailed due to oversupply and low load at midnight. However there is a case where the output of WP is limited during daytime due to the increase in share of photovoltaic(PV). In current electricity market, as the share of PV is increased, the curtailments of WP will be increased further, which will add to the difficulties of wind farm operators. In this paper, we propose a method to distribute the power limit of RE according to the criterion based on the priority constraint of the energy source which is difficult to operate the power system.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.94-99
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• 2024

Recently, wind power has been gaining attention as a highly efficient renewable energy source, leading to various technological developments worldwide. Typically, wind power is operated in the form of large wind farms with many wind turbines installed in areas rich in wind resources. However, in developing countries or regions isolated from the power grid, off-grid small wind power systems are emerging as an efficient solution. To efficiently operate and expand off-grid small-scale power systems, the development of real-time monitoring systems is required. For the efficient operation of small wind power systems, it is essential to develop real-time monitoring systems that can actively respond to excessive wind speeds and various environmental factors, as well as ensure the stable supply of produced power to small areas or facilities through an Energy Storage System (ESS). The implemented system monitors turbine RPM, power generation, brake operation, and more to create an optimal operating environment. The developed small wind power system can be utilized in remote road lighting, marine leisure facilities, mobile communication base stations, and other applications, contributing to the development of the RE100 industry ecosystem.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2348-2354
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• 2016

In recent days, IoT (Internet of Things) technology has been widely used in the field of agriculture, which enables the collection of environmental data and biometric data into the database. The availability of big data on agriculture results in the increase of the machine learning based analysis. Through the analysis, it is possible to forecast agricultural production and the diseases of livestock, thus helping the efficient decision making in the management of smart farm. Herein, we use the environmental and biometric data of Smart Pig farm to derive the accurate relationship model between the environmental information and the daily weight increase of swine and verify the accuracy of the derived model. To this end, we applied the M5P tree algorithm of machine learning which reveals that the wind speed is the major factor which affects the daily weight increase of swine.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.47 no.6
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• pp.1026-1036
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• 2014

Real-time monitoring for environmental factors (temperature, salinity, chlorophyll-a, etc.) and fugacity of carbon dioxide ($fCO_2$) was conducted at an oyster Crassostrea gigas farm in Goseong Bay, south coast of Korea during 2-4th of November, 2011. Surface temperature and salinity were ranged from $17.9-18.7^{\circ}C$ and 32.7-33.8, respectively, with daily and inter-daily variations due to tidal currents. Surface $fCO_2$ showed a range of $390-510{\mu}atm$ and was higher than air $CO_2$ during the study period. Surface temperature, salinity and $fCO_2$ are showed significant correlations with chl.-a and nutrients, respectively. It means when chl.-a value is high in surface water of the oyster farm, active biological production consume $CO_2$ and nutrients from environments and produce oxygen, suggesting a tight feedback between biological processes and environmental reaction. Thus, factors affecting the surface $fCO_2$ were evaluated using a simple mass balance. Temperature and biological productions by phytoplankton are the main factors for $CO_2$ drawdown from afternoon to early night, while biological respiration increases seawater $CO_2$ at night. Air-sea exchange fraction acts as a $CO_2$ decreasing gear during the study period and is much effective when the wind speed is higher than $2-3m\;s^{-1}$. Future studies about organic carbon and biological production/respiration are required for evaluating the roles of oyster farms on carbon sink and coastal carbon cycle.

• Journal of the Korean Geosynthetics Society
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• v.12 no.4
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• pp.45-56
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• 2013

Recently, offshore wind farms are increasingly expected, because there are huge resource and large site in offshore. Jeju island has optimum condition for constructing a wind energy farm. Unlike the mainland, Jeju island has stratified structure distribution between rock layers sediments due to volcanic activation. In these case, it can be occur engineering problems in whole structures as well as the safety of foundation as the thickness and distribution of sediment under top rock layer can not support sufficiently the structure. In this paper, the settlement and stress distribution is predicted by numerical analysis when the mono-pile base are constructed on various soft layer between stratified structure. To determine the settlement of the pile foundation supported on stratified rock layer, the geological investigation at the 3 regiions and the results of laboratory experiments of the stratified rock layer is required.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.689-700
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• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.8
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• pp.1132-1140
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• 2011

When the offshore wind power plant is planned to construct, it is important for the wind farm site to figure out the distribution of the weak soil layers that might cause subsidence by the impact of the external moment from the wind plant's load and an oscillating wind load. Coring test is the optimistic method to figure out weak soil layers, but this method have some problem such as condition of the in-situ or economical limitation. In order to make up for the weak points in coring test, the researches using the geostatistics methods is actually done. In this study, setting a fixed coastal area that offshore wind plants construct firstly and Estimation of distribution on the thickness of the weak soil layer through the geostatistic method is conducted. The weak soil layer is sorted by result of the Standard penetration test, geostatistic method is used to ordinary kring and sequential gaussian simulation and compared to both method's result. As a results of study, we found that both methods show similar estimations of deep weak soil layer and we could evaluate quantitatively the uncertainty of the result.

• Earthquakes and Structures
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• v.10 no.5
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• pp.1143-1179
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• 2016

Offshore wind turbines are considered as a fundamental part to develop substantial, alternative energy sources. In this highly flexible structures, monopiles are usually used as support foundations. Since the monopiles are large diameter (3.5 to 7 m) deep foundations, they result in extremely stiff short monopiles where the slenderness (length to diameter) may range between 5 and 10. Consequently, their elastic deformation patterns under lateral loading differ from those of small diameter monopiles usually employed for supporting structures in offshore oil and gas industry. For this reason, design recommendations (API and DNV) are not appropriate for designing foundations for offshore wind turbine structures as they have been established on the basis of full-scale load tests on long, slender and flexible piles. Furthermore, as these facilities are very sensitive to rotations and dynamic changes in the soil-pile system, the accurate prediction of monopile head displacement and rotation constitutes a design criterion of paramount importance. In this paper, the Fourier Series Aided Finite Element Method (FSAFEM) is employed for the determination of static impedance functions of monopiles for OWT subjected to horizontal force and/or to an overturning moment, where a non-homogeneous soil profile has been considered. On the basis of an extensive parametric study, and in order to address the problem of head stiffness of short monopiles, approximate analytical formulae are obtained for lateral stiffness $K_L$, rotational stiffness $K_R$ and cross coupling stiffness $K_{LR}$ for both rough and smooth interfaces. Theses expressions which depend only on the values of the monopile slenderness $L/D_p$ rather than the relative soil/monopile rigidity $E_p/E_s$ usually found in the offshore platforms designing codes (DNV code for example) have been incorporated in the expressions of the OWT natural frequency of four wind farm sites. Excellent agreement has been found between the computed and the measured natural frequencies.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.1
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• pp.1-10
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• 2015

This paper proposes a control algorithm for permanent magnet synchronous generators with a back-to-back three-level neutral-point clamped voltage source converter in a medium-voltage off-shore wind power system under unbalanced grid conditions. Specifically, the proposed control algorithm compensates for unbalanced grid voltage at the PCC (Point of Common Coupling) in a collector bus of an off-shore wind power system. This control algorithm has been formulated based on symmetrical components in positive and negative synchronous rotating reference frames under generalized unbalanced operating conditions. Instantaneous active and reactive power is described in terms of symmetrical components of measured grid input voltages and currents. Negative sequential component of AC input current is injected into the PCC in the proposed control strategy. The amplitude of negative sequential component is calculated to minimize the negative sequential component of grid voltage under the limitation of current capability in a voltage source converter. The proposed control algorithm enables the provision of balanced voltage at the PCC resulting in the high quality generated power from off-shore wind power systems under unbalanced network conditions.