• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.8
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• pp.391-397
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• 2002

This paper presents a modeling and simulation of a PI controller for maximum power extraction of a grid-connected wind energy conversion system with a link of a rectifier and an inverter. It discusses the maximum power control algorithm fnr a wind turbine and proposes, in a graphical form, the relationships of wind turbine output, rotor speed, power coefficient, tip-speed ratio with wind speed when the wind turbine is operated under the maximum power control. The control objective is to always extract maximum power from wind and transfer the power to the utility by controlling both the Pitch angle of the wind turbine blades and the inverter firing angle. Pitch control method is mechanically complicated, but the control performance is better than that of the stall regulation method. The simulation results performed on MATLAB will show the variation of generator's rotor angle and rotor speed, pitch angle, and generator output.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1173-1178
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• 2011

The power generated by wind turbines changes rapidly because of the continuous fluctuation of wind speed and direction. It is important for the power industry to have the capability to predict the changing wind power. In this paper, neural network based wind power prediction scheme which uses wind speed and direction is considered. In order to get a better prediction result, compression function which can be applied to the measurement data is introduced. Empirical data obtained from wind farm located in Kunsan is considered to verify the performance of the compression function.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1891-1899
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• 2014

A reliability model of wind farm located in mountainous land with complex terrain, which considers the cable and wind turbine (WT) failures, is proposed in this paper. Simple wake effect has been developed to be applied to the wind farm in mountainous land. The component failures in the wind farm like the cable and WT failures which contribute to the wind farm power output (WFPO) and reliability is investigated. Combing the wind speed distribution and the characteristic of wind turbine power output (WTPO), Monte Carlo simulation (MCS) is used to obtain the WFPO. Based on clustering algorithm the multi-state model of a wind farm is proposed. The accuracy of the model is analyzed and then applied to IEEE-RTS 79 for adequacy assessment.

• New & Renewable Energy
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• v.19 no.1
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• pp.22-30
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• 2023

Recently, the use of renewable energy has been increasing to achieve carbon neutrality. The concept of a zero-energy building is also attracting attention. In this study, a preliminary study was conducted to analyze the feasibility of a hybrid wind and solar power generation system between buildings that utilize the building wind generated by the Venturi effect. For this purpose, the wind speed and sunshine hours were monitored in the area where the building wind blows by the Venturi effect, and the power generation depending on system types, areas, and season was estimated. Consequently, the wind power generation system showed a larger amount of power per area than solar power. The wind power systems can generate larger power if wind power blades are installed along the height of the building. As a preliminary study, this study verified the feasibility of the system utilizing building wind and suggested follow-up studies.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.869-877
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• 2016

Necessity has compelled man to improve upon the art of tapping wind energy for power generation; an apt reliever of strain exerted on the non-renewable fossil fuel. The power generation in a Wind Farm (WF) depends on site and wind velocity which varies with time and season which in turn determine wind power modeling. It implies, the development of an accurate wind speed model to predict wind power fluctuations at a particular site is significant. In this paper, Box-Jenkins ARIMA (Auto Regressive Integrated Moving Average) time series model for wind speed is developed for a 99MW wind farm in the southern region of India. Because of the uncertainty in wind power developed, the economic viability and reliability of power generation is significant. Life Cycle Costing (LCC) method is used to determine the economic viability of WF generated power. Reliability models of WF are developed with the help of load curve of the utility grid and Capacity Outage Probability Table (COPT). ARIMA wind speed model is used for developing COPT. The values of annual reliability indices and variations of risk index of the WF with system peak load are calculated. Such reliability models of large WF can be used in generation system planning.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.34-39
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• 2013

This paper proposes the implementation of robust fuzzy controller for designing intelligent wind farm and mitiagating the fluctuation of wind power generator. The existing researches are limited to individual wind turbine with variable speed so that it is necessary to study the multi-agent wind turbine power system. The scopes of these studies include from the arrangements of each power turbine to the control algorithms for the wind farm. For solving these problems, we introduce the composition of intelligent wind farm and use the T-S (Takagi-Sugeno) fuzzy model which is suitable for designing fuzzy controller. The control object in wind farm enables the minimizing the fluctuation of wind power generator. Simulation results for wind fram which is modelled as mathematically are demonstrated to visualize the feasibility of the proposed method.

• New & Renewable Energy
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• v.2 no.3
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• pp.23-30
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• 2006

Need developments of substitute energy to solve problem of global warming by excess use of fossil energy, excess discharge of carbon dioxide. wind power generation system is all-important energy in next generation as clean energy. Environmental pollution of wind power generation system is not exhausted entirely. And, electric-power generation system cost is cheap than other energy. Wind Generation system that is supplied much present is most horizontality style blade structure. But, Horizontal style structure is serious noise and there is problem in stability of blade. We designed special blade solve to this problem. And, manufactured vertical axis wind power generation system because using blade. Also, developed assistance power generator to increase driving efficiency ago wind power generation. We expect this devices that is such cover shortcoming of wind power generation system.

• Journal of Power Electronics
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• v.13 no.5
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• pp.737-745
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• 2013

Offshore wind farms are rapidly growing owing to their comparatively more stable wind conditions than onshore and land-based wind farms. The power capacity of offshore wind turbines has been increased to 5MW in order to capture a larger amount of wind energy, which results in an increase of each component's size. Furthermore, the weight of the marine turbine components installed in the nacelle directly influences the total mechanical design, as well as the operation and maintenance (O&M) costs. A reduction in the weight of the nacelle allows for cost-effective tower and foundation structures. On the other hand, longer transmission distances from an offshore wind turbine to the load leads to higher energy losses. In this regard, DC transmission is more useful than AC transmission in terms of efficiency because no reactive power is generated/consumed by DC transmission cables. This paper describes some of the challenges and difficulties faced in designing high-power-density power conversion systems (HPDPCSs) for offshore wind turbines. A new approach for high gain/high voltage systems is introduced using transformerless power conversion technologies. Finally, the proposed converter is evaluated in terms of step-up conversion ratio, device number, modulation, and costs.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1357-1368
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• 2017

The lack of controllability over the wind causes fluctuations in the output power of the wind generators (WGs) located at the wind farms. Distribution Static Compensator (DSTATCOM) equipped with Battery Energy Storage System (BESS) can significantly smooth these fluctuations by injecting or absorbing appropriate amount of active power, thus, controlling the power flow of WGs. But because of the component aging and thermal drift, its harmonic filter parameters vary, resulting in performance degradation. In this paper, Quantitative Feedback Theory (QFT) is used as a robust control scheme in order to deactivate the effects of filter parameters variations on the wind power generation power smoothing performance. The proposed robust control strategy of the DSTATCOM is successfully applied to a microgrid, including WGs. The simulation results obviously show that the proposed control technique can effectively smooth the fluctuations in the wind turbines' (WT) output power caused by wind speed variations; taking into account the filter parameters variations (structural parameter uncertainties).

• Journal of the Korean Solar Energy Society
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• v.29 no.6
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• pp.62-68
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• 2009

There has been a continuous increase in the utilization and utility value of renewable energy such as wind power generation in modem society. Wind condition is the absolute variable to the energy volume in the case of a wind power generation system. For this reason, wind power generators have already been installed in areas where wind velocity is high and the possibility of danger is very low. In other words, instability is likely if the wind velocity in an area is high and where a wind power generation system can be built. On the contrary, low wind velocity is possible in an area with high stability. Therefore, the design and manufacture of a wind power generation system should be carried out in a more complicated topography in order to secure a bigger market. This study examines and suggest how topography affects wind shear by analyzing the measured data in order to predict wind power generation more reliably.