• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.23 no.4
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• pp.153-178
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• 2018

Most operational uses of wind speed data require measurements at, or estimates generated for, the reference height of 10 m above mean sea level (AMSL). On the Ieodo Ocean Research Station (IORS), wind speed is measured by instruments installed on the lighthouse tower of the roof deck at 42.3 m AMSL. This preliminary study indicates how these data can best be converted into synthetic 10 m wind speed data for operational uses via the Korea Hydrographic and Oceanographic Agency (KHOA) website. We tested three well-known conventional empirical neutral wind profile formulas (a power law (PL); a drag coefficient based logarithmic law (DCLL); and a roughness height based logarithmic law (RHLL)), and compared their results to those generated using a well-known, highly tested and validated logarithmic model (LMS) with a stability function (${\psi}_{\nu}$), to assess the potential use of each method for accurately synthesizing reference level wind speeds. From these experiments, we conclude that the reliable LMS technique and the RHLL technique are both useful for generating reference wind speed data from IORS observations, since these methods produced very similar results: comparisons between the RHLL and the LMS results showed relatively small bias values ($-0.001m\;s^{-1}$) and Root Mean Square Deviations (RMSD, $0.122m\;s^{-1}$). We also compared the synthetic wind speed data generated using each of the four neutral wind profile formulas under examination with Advanced SCATterometer (ASCAT) data. Comparisons revealed that the 'LMS without ${\psi}_{\nu}^{\prime}$ produced the best results, with only $0.191m\;s^{-1}$ of bias and $1.111m\;s^{-1}$ of RMSD. As well as comparing these four different approaches, we also explored potential refinements that could be applied within or through each approach. Firstly, we tested the effect of tidal variations in sea level height on wind speed calculations, through comparison of results generated with and without the adjustment of sea level heights for tidal effects. Tidal adjustment of the sea levels used in reference wind speed calculations resulted in remarkably small bias (<$0.0001m\;s^{-1}$) and RMSD (<$0.012m\;s^{-1}$) values when compared to calculations performed without adjustment, indicating that this tidal effect can be ignored for the purposes of IORS reference wind speed estimates. We also estimated surface roughness heights ($z_0$) based on RHLL and LMS calculations in order to explore the best parameterization of this factor, with results leading to our recommendation of a new $z_0$ parameterization derived from observed wind speed data. Lastly, we suggest the necessity of including a suitable, experimentally derived, surface drag coefficient and $z_0$ formulas within conventional wind profile formulas for situations characterized by strong wind (${\geq}33m\;s^{-1}$) conditions, since without this inclusion the wind adjustment approaches used in this study are only optimal for wind speeds ${\leq}25m\;s^{-1}$.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.195-200
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• 2020

With the growing interest in fossil fuel depletion and environmental pollution, railroad cars operating in Korea are in progress as the conversion from diesel to electric vehicles expands. The photovoltaic system, which is applied as an example of the conversion of electric vehicles, is infinite and pollution-free, and can produce energy without generating hazards such as air pollution, noise, heat, and vibration, and maintain fuel transportation and power generation facilities. There is an advantage that is rarely needed. However, the amount of electricity produced depends on the amount of solar radiation by region, and the energy density is low due to the power generation of about 25㎡/ kWp, so a large installation area is required and the installation place has limited problems. In view of these problems, many studies have been applied to fuel cells in the railway field. In particular, the plan to link the fuel cell power generation system railroad power supply system must be linked to the power supply system that supplies power to the railroad, unlike solar and wind power. Therefore, it has a close relationship with railroad cars and the linkage method can vary greatly depending on the system topology. Therefore, in this paper, we study the validity through simulation modeling related to linkage analysis according to system topology.

• 한국태양에너지학회:학술대회논문집
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• 2009.11a
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• pp.56-61
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• 2009

Paradigm depending only on fossil fuel for building heat source is rapidly changing. Accelerating the change, as it has been known, is obligation for reducing green house gas coming from use of fossil fuel, i.e. reaction to United Nations Framework Convention on Climate Change. In addition, factors such as high oil price, unstable supply, weapon of petroleum and oil peak, by replacing fossil fuel, contributes to advance of environmental friendly renewable energy which can be continuously reusable. Therefore, current new energy policies, beyond enhancing effectiveness of heat using equipments, are to make best efforts for national competitiveness. Our country supports 11 areas for new renewable energy including sun light, solar heat and wind power. Among those areas, ocean thermal energy specifies tidal power generation using tide of sea, wave and temperature differences, wave power generation and thermal power generation. But heat use of heat source from sea water itself has been excluded as non-utilized energy. In the future, sea water heat source which has not been used so far will be required to be specified as new renewable energy. This research is to survey local heating system in Europe using sea water, central solar heating plants, seasonal thermal energy store and to analyze large scale central solar heating plants in German. Seasonal thermal energy store necessarily need to be equipped with large scale thermal energy store. Currently operating central solar heating system is a effective method which significantly enhances sharing rate of solar heat in a way that stores excessive heat generating in summer and then replenish insufficient heat for winter. Construction cost for this system is primarily dependent on large scale seasonal heat store and this high priced heat store merely plays its role once per year. Since our country is faced with 3 directional sea, active research and development for using sea water heat as cooling and heating heat source is required for seashore villages and building units. This research suggests how to utilize new energy in a way that stores cooling heat of sea water into seasonal thermal energy store when temperature of sea water is its lowest temperature in February based on West Sea and then uses it as cooling heat source when cooling is necessary. Since this method utilizes seasonal thermal energy store from existing central solar heating plant for heating and cooling purpose respectively twice per year maximizing energy efficiency by achieving 2 seasonal thermal energy store, active research and development is necessarily required for the future.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.38.2-38.2
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• 2010

Biomimetc is a new domain of learning that proposes a solution getting clues from nature. There seems to be a sign of this phenomenon in fields of Renewable Energy. Foe example, Wind power was imitate the whale's fin that was improve efficiency of generating energy. This study focused on the photovoltaic generation as the instance of applying biomimetic. Efficiency is the most important factor in field of Photovoltaic generation. When given solar cell taking the sun light, most important fields of the study are absorb more light and increase the quantity of generation. For improving efficiency, the solar cell were builded up textures of taking a pyramid form, such a surface structure taking a role for remaining the light. This effects do the role as increasing absorbing efficiency. Such phenomenon calls Light Trapping, locking up the light on the surface of solar cell for a long time. Light is a vital factor to plants in the nature. Plants grow up through the photosynthesis that absorbing light for growth and propagation. So, plants make a effort how can absorb more the light in poor surroundings. This study set up a goal that imitates the minute surface structure of plants and applies to the existing solar cells's surface structure, so it can improve the efficiency of absorbing light. We used Light Tools software analyzing geometrical optics to analyze efficiency about new designed textures on the computer. We made a comparison between existing textures and new designed textures. Consequently, new designed textures were advanced efficiency, absorbing rates of light increasing about 7 percent. In comparison with existing and new textures, advancing about 20 percent in the efficient aspect.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.135-142
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• 2015

Human-powered self-generating devices have been attractive with its operation characteristic independent from outer environment such as weather condition and wind speed. However, conventional self-generators have low electric power output due to their weakly-coupled electromagnetic structure. More importantly, rotary crank motion which is usually adopted by conventional self-generator to generate electricity requires specific skeletal muscles to maintain large torque circular motion and consequently, causes fatigue on those muscles before it can generate enough amount of electricity for any practical application. Without improvement in electric power output and usability, the human-powered self-generator could not be used in everyday life. This study aims to develop a human-powered self-generator which realized a strong electromagnetic coupling in a closed-loop tubular structure (hula-hoop shape) for easy and steady long-term driving as well as larger electric output. The performance and usability of the developed human-powered generator is verified through experimental comparison with a commercial one. Additionally, human workload which is a key element of a human-powered generator but not often considered elsewhere, is estimated based on metabolic energy expenditure measured respiratory gas analyzer. Further study will focus on output and portability enhancement, which can contribute to the continuous power supply of mobile equipments.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Clean Technology
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• v.26 no.1
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• pp.72-78
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• 2020

The use of fossil fuel and biogas production causes air pollution and climate change problems. Research endeavors continue to focus on converting methane and carbon dioxide, which are the major causes of climate change, into quality energy sources. In this study, a novel plasma-carbon converter was proposed to convert biogas into high quality gas, which is linked to photovoltaic and wind power and which poses a problem on generating electric power continuously. The characteristics of conversion and gas production were investigated to find a possibility for biogas conversion, involving parametric tests according to the change in the main influence variables, such as O₂/C ratio, total gas feed rate, and CO₂/CH₄ ratio. A higher O₂/C ratio gave higher conversions of methane and carbon dioxide. Total gas feed rate showed maximum conversion at a certain specified value. When CO₂/CH₄ feed ratio was decreased, both conversions increased. As a result, the production of solar fuel by plasma oxidation destruction-carbon material gasification conversion, which was newly suggested in this study, could be known as a possibly useful technology. When O₂/C ratio was 0.8 and CO₂/CH₄ was 0.67 while the total gas supply was at 40 L min^-1 (VHSV = 1.37), the maximum conversions of carbon dioxide and methane were achieved. The results gave the highest production for hydrogen and carbon dioxide which were high-quality fuel.