• International Journal of Advanced Culture Technology
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• v.4 no.1
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• pp.37-50
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• 2016

In recent years, the development and application of green energy resources have attracted more and more /$^*$ 'tention of people. The training room presented here is focused on the terminal applications of a photovoltaic power generation system (PPGS). Through introducing the composition and the general design principles, we aimed at leading the students to master the fundamental skills required for its design, installation and construction. The training room consists of numerous platforms, such as: PPGS, Wind and Photovoltaic Hybrid Power Generation Systems, Wind Power Generation Equipments, Simulative Grid-Connected Power Generation System, Electronic Technology Application of New Energy, etc. This enables the students to obtain their project and professional skills training via assembling, adjusting, maintaining and inspecting, etc., various component parts of the photovoltaic and new energy power generation systems, to further grasp the fundamental and related theoretical knowledge, and to further reinforce their practical and operational skills, so as to improve their problem-analyzing and problem-solving abilities.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.211-218
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• 2012

Fossil fuel is used all over the world and it produces greenhouse gases due to fossil fuel use. Therefore, it cause global warming and is serious environmental pollution. In order to decrease the environmental pollution, we should use renewable energy which is clean energy. Among several renewable energy, wind energy is the most promising one. Wind power generation is does not produce environmental pollution and could not be exhausted. However, due to wind power generation has irregular power output, it is important to predict generated electrical energy accurately for smoothing wind energy supply. There, we consider use ramp characteristic to forecast accurate wind power output. The ramp increase and decrease rapidly wind power generation during in a short time. Therefore, it can cause problem of unbalanced power supply and demand and get damaged wind turbine. In this paper, we make prediction models using power ramp rate as well as wind speed and wind direction to increase prediction accuracy. Prediction model construction algorithm used multilayer neural network. We built four prediction models with PRR, wind speed, and wind direction and then evaluated performance of prediction models. The predicted values, which is prediction model with all of attribute, is nearly to the observed values. Therefore, if we use PRR attribute, we can increase prediction accuracy of wind power generation.

• The KSFM Journal of Fluid Machinery
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• v.4 no.3 s.12
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• pp.62-77
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• 2001

The modern wind turbines are widely used as important natural energy sources for the electric generation in western countries and some Asian nations. They are commercially matured and progressive and clear policy for the more development with higher technical purposes is maintained throughout the world. Modern wind turbines produce nearly 2000 kW output in their largest sizes and this trend increases up to more powerful power and ultimate utilization of wind energy favoured by clean natural energy. This article has the points of reviewing the states of the art of modern wind turbines with their present technical directions toward next generation version. Some descriptionsare given for easy understanding of the turbine components and related fluid mechanics concerned. The general outlines of policy taken over some countries are also introduced.

• Journal of the Korean Solar Energy Society
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• v.24 no.3
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• pp.47-54
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• 2004

Photovoltaic energy and wind energy are highly dependent on the season, time and extremely intermittent energy sources. Because of these reasons, in view of the reliability the photovoltaic and the wind power generation system have many problems(energy conversion, energy storage, load control etc.) comparing with conventional power plant. In order to solve these existing problems, hybrid generation system composed of photovoltaic(500W) and wind power system(400W) was suggested. But, hybrid generation system cannot always generate stable output due to the varying weather condition. So, the auxiliary power compensation unit that uses elastic energy of spiral spring was added to hybrid generation system for the present study. It was partly confirmed that hybrid generation system was generated a stable outputs by spiral spring was continuously provided to load.

• New & Renewable Energy
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• v.10 no.2
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• pp.19-28
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• 2014

Wind power generation of 5 MW wind turbine was predicted by using wind measurement data from HeMOSU-1 which is at south west coast of Korea. Time histories of turbulent wind was generated from 10-min mean wind speed and then they were used as input to Bladed to estimated electric power. Those estimated powers are used in both polynominal regression and neural network training. They were compared with each other for daily production and yearly production. Effect of mean wind speed and turbulence intensity were quantitatively analyzed and discussed. This technique further can be used to assess lifetime power of wind turbine.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.5
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• pp.79-89
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• 2012

The objectives of this paper were to evaluate the wind flow behind the livestock ventilation fan for small-scale wind power generation and to make flow profiles of imaginary ventilation fan for future simulation works. The field experiments using typical 50-inch fan indicated that the wind flow behind the ventilation fan had a good possibility of power generation with its high and steady wind speeds up to a distance of 2 m. The expected electricity yield was almost 101~369 W with a small (0.8 m radius) wind turbine. The decline of ventilation fan performance caused by the obstacle was also not significant with about 4 % from a distance of 2 m. The flow profiles for the computational fluid dynamics (CFD) simulation was created by combining the direction vectors analyzed from tuft visualization test and the flow predicted by the rotating fan modeling. The flow profiles are expected to provide an efficient saving of computational time and cost to design a better wind turbine system in future works.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.2
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• pp.167-174
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• 2016

Even though the differential drag type machines of the vertical wind turbines are a bit less efficient than the lift type machines such as Darrieus type machines, they have an advantage of low starting torque. The flapping blade type wind turbine is a specific type of the differential drag machines, and it has no need for orientation as well as quite low starting torque. This work is to develop an innovative 5kW class flapping type vertical wind turbine system which will be applicable to a hybrid power generation system driven by the diesel engine and the wind turbine. The parametric study was carried out to decide an optimum aerodynamic configuration of the wind turbine blade. In order to evaluate the designed blade, the subscale wind tunnel test and the performance test were carried out, and their test results were compared with the analysis results.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.60-70
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• 2014

This paper discusses the impacts of large scale grid-connected wind farm equipped with permanent magnet synchronous generator (PMSG) on power system small signal stability (SSS) incorporating wind generation uncertainty and volatility. Firstly, a practical simplified PMSG model with rotor-flux-oriented control strategy applied is derived. In modeling PMSG generator side converter, the generator-voltage-oriented control strategy is utilized to implement the decoupled control of active and reactive power output. In modeling PMSG grid side converter, the grid-voltage-oriented control strategy is applied to realize the control of DC link voltage and the reactive power regulation. Based on the Weibull distribution of wind speed, the Monte Carlo simulation technique based is carried out on the IEEE 16-generator-68-bus test system as benchmark to study the impacts of wind generation uncertainty and volatility on small signal stability. Finally, some preliminary conclusions and comments are given.

• New & Renewable Energy
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• v.20 no.2
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• pp.44-54
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• 2024

The objective of this study was to contribute to domestic offshore wind farms by reasonably predicting the expected completion time and installed power generation capacity of offshore wind projects in South Korea. Offshore wind power is drastically regarded as a core tool for clean energy transition and industrial decarbonization in the fight against the climate crisis globally. Especially in South Korea offshore wind power is the main tool in partaking in RE100 and K-RE100, and the Korean government aims to install 14.9 GW of offshore wind farms by 2030. However, this seems to have been significantly delayed due to the complex process of obtaining permits for offshore wind power in Korea. Thus, a reasonable prediction of power generation and a timeline for the final construction are imperative. To establish the delay time for permit licenses, classified location factors were included into site analysis. These factors comprised reviews of transmission and military operability, environmental impact assessment, maritime traffic safety examination, wind resource assessment and an analysis of current offshore wind projects. According to the analysis, the majority of offshore wind projects currently being developed in Korea are predicted to be delayed by 3-5 years as they are among the criteria included in key discussion points for obtaining permits. The cumulative installed power capacity and annual power generation after construction are expected to be 37 GW and 97 TWh respectively.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.345-347
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• 2006

In this paper, a novel method for wind speed estimation in wind power generation systems is presented. The proposed algorithm is based on estimating the wind speed using Support-Vector-Machines for regression (SVR). The wind speed is estimated using the generator power-speed characteristics as a set of training vectors. SVR is trained off-line to predict a continuos-valued function between the system's inputs and wind speed value. The predicted off-line function as well as the instantaneous generator power and speed are then used to determine the unknown winds speed on-line. The simulation results show that SVR can define the corresponding wind speed rapidly and accurately to determine the optimum generator speed reference for maximum power point tracking.