• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1373-1383
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• 2016

The wind energy industry and wind power generation have increased; consequently, the stable supply of the wind power has become an important issue. It is important to accurately predict the wind power with short-term basis in order to make a reliable planning for the power supply and demand of wind power. In this paper, we first analyzed the speed, power and the directions of the wind. The neural network and the time series models (ARMA, ARMAX, ARMA-GARCH, Holt Winters) for wind power generation forecasting were compared based on mean absolute error (MAE). For one to three hour-ahead forecast, ARMA-GARCH model was outperformed, and the neural network method showed a better performance in the six hour-ahead forecast.

• STI Policy Review
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• v.6 no.2
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• pp.146-173
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• 2015

This study explores how to reconcile science and policy in the wind energy sector by providing a conceptual framework for better understanding evidence-based policymaking (EBPM). Regarding this framework, the core issue is to discover how knowledge is formed over time, and which factors affect this knowledge formation. Comparative cases of wind industry emergence in Spain and Britain are examined. This analysis shows that knowledge formation initially starts in the scientific arena in parallel with its formation in the practical, and is followed by political knowledge formation near the beginning of commercial projects. Regarding knowledge formation, three more comparisons are made between wind industry emergence in Spain and Britain: the different approaches to R&D projects, the different adoptions of supporting measures, and the different ways of coping with public opposition. The factors affecting the comparisons are mainly perceptions of energy supply, nuclear power, environment and science and technology. Communication and unfamiliarity are likely to affect the comparisons in EBPM.

• Journal of Energy Engineering
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• v.23 no.1
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• pp.46-57
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• 2014

This study analyzes whether the value-added structure of Korean wind power industry exhibits a virtuous cycle through the value chain(VC) within wind power firms and the value system(VS) among the wind power industries, using a regression analysis based on a survey about Korean wind power companies. According to the VC, the government's R&D support is analyzed to have contributed to an increase in the R&D investments of the wind power companies. An increase in corporates' R&D investments has led to an increase in corporates' R&D outputs, and in turn, induced a remarkable increase in the amounts of production. But an increase in production has not led to a decrease in the costs of production, not resulting in an increase in profit rates per sales amount. In addition, while an increase in profit rates is analyzed to have contributed to an increase in production, this did not induce further investments in corporate's R&D. The virtuous cycle of the value chain in Korean wind power firms is, therefore, analyzed to be weak. Next, the VS is analyzed by dividing the whole chain into the system group including rotor blades, gear boxes, and power generators, and the structure group, such as towers. Two groups are analyzed to have mutually positive effects in the processes of the government's support for corporates' R&D, corporates' investment in R&D, R&D outputs, and profit rates per sales amount. Such mutual positive effects are, however, not found in the processes of the amounts of production and the costs of production. These results demonstrates that the value system of Korean wind power industry is not completed. This study has a policy implication to need further efforts to create the virtuous cycle in the VC and VS of Korean wind power industry.

• Ocean Systems Engineering
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• v.13 no.1
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• pp.21-41
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• 2023

Decarbonization and energy transition can be considered as a main concern even for the oil industry. One of the initiatives to reduce emissions under studies considers the use of renewable energy as a complimentary supply of electric energy of the production platforms. Wind energy has a higher TRL (Technology Readiness Level) than other types of energy converters and has been considered in these studies. However, other types of renewable energy have potential to be used and hybrid concepts considering wind platforms can help to push the technological development of other types of energy converters and improve their efficiency. In this article, a preliminary hydrodynamic assessment of a new concept of hybrid wind and wave energy conversion platform was performed, in order to evaluate the potential of wave power extraction. A multiple OWCs (Oscillating Water Column) WEC (Wave Energy Converter) design was adopted for the analysis and some simplifications were adopted to permit using a frequency domain approach to evaluate the mean wave power estimation for the location. Other strategies were used in the OWC design to create resonance in the sea energy range to try to maximize the potential power to be extracted, with good results.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.1-8
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• 2019

In this paper, we study the BESS of a standalone hybrid street light. The proposed BESS proposed a BESS with the function of efficiently charging irregularly generated power from two or more generators. AC generated by wind power is converted to DC using an AC / DC converter and then to a voltage that can charge the battery through the DC / DC converter. The lack of voltage and current, which is a disadvantage of the MPPT method used in solar power generation, is compensated by the DC value of wind power generation. The compensation method is to convert the DC generated from solar power into a voltage suitable for charging the battery through a DC / DC converter, and then connect the DC generated in wind power in parallel to compensate for the insufficient current to charge the battery in a short time. Allow this to begin. By securing the maximum charging time, the usage time of the stand-alone hybrid street light is huge. Experimental results show that the battery has a short charging time and can be efficiently applied to battery-dependent standalone hybrid street lights.

• Journal of Navigation and Port Research
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• v.35 no.5
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• pp.381-385
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• 2011

In this paper, an economic feasibility study of wind-diesel hybrid power systems for an island in the Yellow Sea, where the maximum power generation is about 500kW, was performed. For the study, annual electric load variation and wind resource data of the island were collected and analyzed. HOMER program - a typical hybrid optimization model for electric renewables including wind resource, developed by the National Renewable Energy Laboratory - was used. Wind speed and diesel price were picked out as variables for the sensitivity analysis in order to find the economic accountability for the wind-diesel hybrid power system. As the result, even though it is not feasible economically under the present condition, if mean wind speed is over 3 m/sec. or diesel price goes up to 2.4 $ per liter, the wind-diesel hybrid power system for the island becomes a prospective candidate.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.766-772
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• 2009

Generally, wind industry has been oriented to large power systems which require large windy areas and often need to overcome environment restrictions. However, small-scale wind turbines are closer to the consumers and have a large market potential, and much more efforts are required to become economically attractive. In this paper, a prototype of a small-scale urban wind generation system for battery charging application is described and a neural network based MPPT(Maximum Power Point Tracking) algorithm which can be effectively applied to urban wind turbine system is proposed. Through Matlab based simulation studies and actual implementation of the proposed algorithm, the feasibility of the proposed scheme is verified.

• Wind and Structures
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• v.27 no.2
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• pp.111-121
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• 2018

Experiments were conducted in a large-scale Ward-type tornado simulator to study tornado-like vortices. Both flow velocities and the pressures at the surface beneath the vortices were measured. An interpretation of these measurements enabled an assessment of the mean flow field as well as the mean and fluctuating characteristics of the surface pressure deficit, which is a manifestation of the flow fluctuation aloft. An emphasis was placed on the effect of the aspect ratio of the tornado simulator on the characteristics of the simulated flow and the corresponding surface pressure deficit, especially the evolution of these characteristics due to the transition of the flow from a single-celled vortex to a two-celled vortex with increasing swirl ratio.

• STI Policy Review
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• v.3 no.1
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• pp.63-79
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• 2012

Regional innovation systems and clusters represent a fashionable conceptual basis for regional innovation policies in many industrialized countries (including South Korea). Due to questions related to climate change and environment-friendly energy production, the green industry has been increasingly discussed in relation to regional innovation systems and clusters. This explorative paper analyzes these discussions and critically examines the emergence of green clusters in South Korea based on the case of the wind power cluster in Jeonbuk Province. It tentatively concludes that the role of the central government is too powerful and the role of regional actors (policy-makers and entrepreneurs) is too weak for the successful emergence of green clusters.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1385-1397
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• 2018

There are many factors that affect the wind speed. In addition, the randomness of wind speed also leads to low prediction accuracy for wind speed. According to this situation, this paper constructs the short-time forecasting model based on the least squares support vector machines (LSSVM) to forecast the wind speed. The basis of the model used in this paper is support vector regression (SVR), which is used to calculate the regression relationships between the historical data and forecasting data of wind speed. In order to improve the forecast precision, historical data is clustered by cluster analysis so that the historical data whose changing trend is similar with the forecasting data can be filtered out. The filtered historical data is used as the training samples for SVR and the parameters would be optimized by particle swarm optimization (PSO). The forecasting model is tested by actual data and the forecast precision is more accurate than the industry standards. The results prove the feasibility and reliability of the model.