• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3672-3681
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• 2022

This study investigates the environmental footprint impacts of nuclear energy consumption in the presence of environmental technology and globalization of the ten largest ecological footprint countries from 1990 up to 2017. By considering a set of methods that can help solve the issue of cross-sectional dependence, we employ the Lagrange multiplier bootstrap cointegration method, Driscoll-Kraay standard errors for long-run estimation and feasible generalized least squares (FGLS) and panel-corrected standard errors (PCSE) for robustness. The finding revealed significant negative effects of nuclear energy consumption, environmental-related technology, population density and significant positive effects of globalization and economic growth on ecological footprint. These results are also robust by assessing the long-run impacts of predictors on carbon footprint and CO₂ emissions as alternate ecological measures. These conclusions provide the profound significance of nuclear energy consumption for environmentally sustainable development in the top ten ecological footprint countries and serve as an important reference for ecological security for other countries globally.

• Journal of the Korean Solar Energy Society
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• v.39 no.5
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• pp.29-40
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• 2019

In response to the rapid climate change, in order to save energy in the field of buildings, the country is planning not only zero energy buildings but also zero energy cities. In the Urban Development Project, the Energy Use Plan Report is prepared and submitted by predicting the amount of energy demand at the planning stage. However, due to the activation of zero-energy buildings and the increase in the supply of new and renewable energy facilities, the energy consumption behavior of buildings in the city is changing from the previous ones. In this study, to estimate urban energy demand of Zero Energy City, building energy demand forecasts based on "Passive plans for use of energy based primary energy consumption", "Actual building energy usage data from Korea Appraisal Board" and "data from Certification of Building Energy Efficiency Rating" as well as demand forecast according to existing "Consultation about Energy Use Plan Code" were calculated and then applied to Multifunctional Administrative City 5-1 zone to compare urban total energy demand forecasts.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1132-1136
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• 2014

In the context of increasing electric energy consumption in a data center, energy efficiency improvement is strongly emphasized. In a data center, electric energy is largely consumed by DC power supply system, which is based on a rectifier composed by multiple parallel converters. Therefore, rectifier efficiency must be improved for minimizing loss of DC power supply system. Rectifier efficiency can be modulated by load allocation to converters because converter efficiency depends on input AC power. In this paper, we propose a new control method to maximize rectifier efficiency. The method can control load allocation to converters by introducing active power converter control scheme and start-and-stop of converters. In order to illustrate optimal load allocations in a rectifier, a maximization problem of rectifier efficiency is formulated as a nonlinear optimization one. The problem is solved by Lagrangian relaxation method and the computation results provide the validity of proposed method.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.5
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• pp.414-424
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• 2015

In this research, we consider a smart grid network of electricity with multiple consumers connected to a monopolistic provider. Each consumer can be informed the real time price changes through the smart meter and updates his consumption schedule to minimize the energy consumption expenditures by which the required power demand should be satisfied under the given real time pricing scheme. This real-time decision making problem has been recently studied through game-theoretic approach. The present paper contributes to the existing literature by incorporating storage appliance into the set of available household appliances which has somewhat distinctive functions compared to other types of appliances and would be regarded to play a significant role in energy consumption scheduling for the future smart grid. We propose a game-theoretic algorithm which could draw the optimal energy consumption scheduling for each household appliances including storage. Results on simulation data showed that the storage contributed to increase the efficiency of energy consumption pattern in the viewpoint of not only individual consumer but also whole system.

• Journal of the Semiconductor & Display Technology
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• v.19 no.1
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• pp.23-28
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• 2020

In Smart mobile devices embedding big.LITTLE architectures, the conventional multi-core assignment scheme for user applications may incur wasteful energy consumption and long response time. In this paper, we propose a user experience assisted energy-efficient multicore assignment scheme. Our simulation results show that the proposed scheme achieves at 40% less energy consumption and at 20% less response time comparing to the legacy scheme.

• KIEAE Journal
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• v.15 no.2
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• pp.45-52
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• 2015

Purpose: Currently, since the energy consumption of apartment buildings is on the rise, it is necessary to reduce the total amount of the energy through the survey and analysis of energy consumption data. Although various studies for energy efficiency have been conducted, studies are more focused on the measurement of energy by using analysis tools. In addition, the studies are sufficient to analyze real data of the city gas in apartment buildings. Therefore, the objective of this study is to identify the property of annual and $1m^2$ city gas amount according to the exclusive dwelling area. Method: To achieve the objective, this study used the statistics such as descriptive, correlation, and analysis of variance (ANOVA) analysis. Result: As a result, there is positive relationship between the annual average of city gas and the exclusive dwelling area. However, in the case of $1m^2$ city gas amount, a negative relationship is mored. In the future, the findings of this study can be applied to develop the prediction model of the city gas consumption and implement it as basic data for energy efficiency of apartment buildings of future.

• Journal of the Korean Solar Energy Society
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• v.29 no.5
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• pp.8-13
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• 2009

Feasibilities of the application of a micro gas turbine cogeneration system to a large size hospital building are studied by estimating energy demands and supplies. The energy demand for electricity is estimated by surveying and sorting the consumption records for various equipment and devices. The cooling heating, and hot water demands are further refined with TRNSYS and ESP-r to generate load profiles for the subsequent operation simulations. The operation of the suggested cogeneration system in conjunction with the load data is simulated for a time span of a year to predict energy consumption and gain profile. The simulation revealed that the thermal efficiency of the gas turbine is about 30% and it supplies 60% of the electricity required by the building. The recovered heat can meet 56% of total heating load and 67% of cooling, and the combined efficiency reaches up to 70%.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.271-276
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• 2014

The life-time and performance of a wireless sensor network is closely related to energy-efficiency of sensor nodes. In this paper, to increase energy-efficiency, each sensor node operates in one of three operational modes which are normal, power-saving, and inactive. In normal mode sensor nodes sense and transmit data with normal period, whereas sensor nodes in power-saving mode have three-times longer period. In inactive mode, sensor nodes do not sense and transmit any data, which makes the energy consumption to be minimized. Plus, the proposed algorithm can avoid unnecessary energy consumption by preventing transmitting duplicate sensed data. We implemented and simulated the proposed algorithm using Tiny OS based ZigbeX platfom and NS-2, respectively. Performance evaluation results show that the proposed algorithm can prolong sensor networks' lifespan by efficiently reducing energy consumption and its standard deviation of all sensor nodes.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.5
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• pp.467-473
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• 2013

Diverse approaches for reducing the total energy consumption of machine tools have been introduced and developed, to cope with rapid increase of total energy costs in world-wide manufacturing industries. To realize the improvement of the energy efficiency, systematic and integrated strategies must be considered, including energy-saving design, optimized control operation and concrete evaluation of the energy efficiency. This paper proposes key enabling technologies required to improve the energy efficiency of 5-axis multi-functional machining tools, considering both of system design and operation in the real production environments. Related standardized procedures of the energy efficiency evaluation is also represented.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.92-100
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• 2018

In this paper, we propose a fault-tolerant scheduling scheme with energy efficiency for real-time periodic tasks on DVFS-enabled multicore processors. The scheme provides the tolerance of a permanent fault with the primary-backup task model. Also the scheme reduces the energy consumption of real-time tasks with the fully overlapped execution between each primary task and its backup task, whereas most of previous methods tried to minimize the overlapped execution between the two tasks. In order to the leakage energy loss of idle cores, the scheme activates a part of available cores with rarely used cores powered off. Evaluation results show that the proposed scheme saves up to 82% energy consumption of the previous method.