• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1312-1320
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• 2022

The earlier studies have analyzed theoretical links between nuclear energy and carbon dioxide (CO₂) emissions concerning territorial (or production-based) emissions. Here using the latest available dataset, this study explores the impacts of nuclear energy on production-based and consumption-based CO₂ emission in the era of globalization for the Organization for Economic Co-operation and Development (OECD) countries. The Driscoll-Kraay regression method reveals that nuclear energy is beneficial for the reduction of production-based CO₂ emissions. However, it is revealed that nuclear energy does not reduce consumption-based CO₂ emissions that are traded internationally and hence not comprised in conventional production-based emissions (territory) inventories. Globalization tends to reduce both production-based and demand-based carbon emissions. Finally, Environmental Kuznets Curve (EKC) is validated for both kinds of CO₂ emissions. The findings may deliver practical policy implications related to nuclear energy and CO₂ emissions for selected countries.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.453-456
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• 2022

The role of the power grid is to ensure stable power supply. It is necessary to take various measures to prepare for unstable situations without notice. After identifying the relationship between features through exploratory data analysis using weather data, a machine learning based energy production prediction model is modeled. In this study, the prediction reliability was increased by extracting the features that affect energy production prediction using principal component analysis and then applying it to the machine learning model. By using the proposed model to predict the production energy for a specific period and compare it with the actual production value at that time, the performance of the energy production prediction applying the principal component analysis was confirmed.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.42-47
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• 2018

Recently, as the demand for limited resources continues to rise and problems of resource depletion rise worldwide, the importance of renewable energy is gradually increasing. In order to solve these problems, various methods such as energy conservation and alternative energy development have been suggested, and biogas, which can utilize the gas produced from biomass as fuel, is also receiving attention as the next generation of innovative renewable energy. New and renewable energy using biogas is an energy production method that is expected to be possible in large scale because it can supply energy with high efficiency in compliance with energy supply method of recycling conventional resources. In order to more efficiently produce and manage these biogas, a biogas plant has emerged. In recent years, a large number of biogas plants have been installed and operated in various locations. Organic wastes corresponding to biogas production resources in a biogas plant exist in a wide variety of types, and each of the incoming raw materials is processed in different processes. Because such a process is required, the case where the biogas plant process is inefficiently operated is continuously occurring, and the economic cost consumed for the operation of the biogas production relative to the generated biogas production is further increased. In order to solve such problems, various attempts such as process analysis and feedback based on the feedstock have been continued but it is a passive method and very limited to operate a medium/large scale biogas plant. In this paper, we propose "CNN-based production yield prediction algorithm for increasing process efficiency of biogas plant" for efficient operation of biogas plant process. Based on CNN-based production yield forecasting, which is one of the deep-leaning technologies, it enables mechanical analysis of the process operation process and provides a solution for optimal process operation due to process-related accumulated data analyzed by the automated process.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.5
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• pp.702-710
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• 2000

A large portion of total energy expenditure associated with ruminant livestock production goes towards maintenance. Approximately 55% of whole body energy use is consumed by visceral tissues (including internal organs) with the majority of this going to the liver and gastrointestinal tract. Muscle and adipose tissues consume about 27% of total body energy expenditure. Metabolic components within the viscera responsible for the majority of energy consumption include ion transport, protein turnover, substrate cycling, and urea synthesis (liver). Within muscle tissue of growing animals ion transport and protein turnover account for most of the energy expenditure. Protein synthesis consumes approximately 23% of whole body energy use and visceral tissues account for proportionally more of whole body protein synthesis than skeletal muscle. Research efforts focused on improving energetic efficiency of the tissues and metabolic mechanisms responsible for the majority of whole animal energy expenditure should provide information leading to more efficient production of an edible product.

• Journal of the Korean Solar Energy Society
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• v.33 no.6
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• pp.32-38
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• 2013

In an efforts to encourage renewable energy deployment, the government has initiated so called 1 million green homes program but the accumulated installation capacity of small wind turbine has been about 70kW. It can be explained in several ways such that current subsidy program does not meet public expectations, economic feasibility of wind energy is in doubt or acoustic emission is significant etc. The author investigated annual energy production of Skystream 3.7 wind turbine using measured power curve and wind resource data. The measured power curve of the small wind turbine was obtained through power performance tests at Wol-Ryoung test site. AEP(Annual Energy Production) and CF(Capacity Factor) were evaluated at selected locations with the measured power curve.

• Transactions of the Korean hydrogen and new energy society
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• v.18 no.4
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• pp.464-480
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• 2007

There are several methods for the hydrogen production such as steam reforming of natural gas, photochemical method, biological method, electrolysis and thermochemical method, etc. These days it has been widely studied for the hydrogen production method having low hydrogen production cost and high efficiency. In this paper, patents in the hydrogen production by steam reforming of natural gas were gathered and analyzed. The search range was limited in the open patents of USA(US), European Union(EP), Japan(JP), and Korea(KR) from 1996 to 2006. Patents were gathered by using key-words searching and extracted by filtering criteria. The trends of the patents was analyzed by the years, countries, companies, and technologies.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.4
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• pp.59-66
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• 2008

Anaerobic digestion system is getting more attractive in that it produces biogas in the process of organic waste stabilization. Net energy production is important when biogas production is concerned. In this study, net energy production was evaluated with respect to biogas production and heat losses in a hypothetical digester. Under the condition of digester operation with slurry inflow of 5% of TS, additional fuel is required to maintain digester temperature during the winder season. Substrate therefore, needs to have higher VS contents through co-digestion of silage or food waste that has greater values of methane production rate. Heating input slurry is important in cold season, which covers over 80% of heating requirement. Heat recovery from digestate is valuable to reduce the use of biogas for heating. It seems desirable to minimize slurry inflow when temperature is very low. Psychrophilic digestion may be a feasible option for reducing heating requirement.

• Journal of the Korean Chemical Society
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• v.49 no.4
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• pp.370-376
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• 2005

• Proceedings of the Korean Nuclear Society Conference
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• 2005.10a
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• pp.759-760
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• 2005

• International Journal of Air-Conditioning and Refrigeration
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• v.15 no.1
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• pp.34-45
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• 2007

In order to reduce the compression power and to use the overall energy contained in LNG effectively, a combined cycle is devised and simulated. The combined cycle is composed of two cycles; one is an open cycle of liquid/solid carbon dioxide production cycle utilizing LNG cold energy in $CO_2$ condenser and the other is a closed cycle gas turbine which supplies power to the $CO_2$ cycle, utilizes LNG cold energy for lowering the compressor inlet temperature, and uses the heating value of LNG at the burner. The power consumed for the $CO_2$ cycle is investigated in terms of a solid $CO_2$ production ratio. The present study shows that much reduction in both $CO_2$ compression power (only 35% of the power used in conventional dry ice production cycle) and $CO_2$ condenser pressure could be achieved by utilizing LNG cold energy and that high cycle efficiency (55.3% at maximum power condition) in the gas turbine could be accomplished with the adoption of compressor inlet cooling and regenerator. Exergy analysis shows that irreversibility in the combined cycle increases linearly as a solid $CO_2$ production ratio increases and most of the irreversibility occurs in the condenser and the heat exchanger for compressor inlet cooling. Hence, incoming LNG cold energy to the above components should be used more effectively.