• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5357-5381
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• 2018

Cloud computing offers a wide range of on-demand resources over the internet. Utility-based resource allocation in cloud data centers significantly increases the number of cloud users. Heavy usage of cloud data center encounters many problems such as sacrificing system performance, increasing operational cost and high-energy consumption. Therefore, the result of the system damages the environment extremely due to heavy carbon (CO2) emission. However, dynamic allocation of energy-efficient resources in cloud data centers overcomes these problems. In this paper, we have proposed Energy and Service Level Agreement (SLA) Aware Resource Allocation Heuristic Algorithms. These algorithms are essential for reducing power consumption and SLA violation without diminishing the performance and Quality-of-Service (QoS) in cloud data centers. Our proposed model is organized as follows: a) SLA violation detection model is used to prevent Virtual Machines (VMs) from overloaded and underloaded host usage; b) for reducing power consumption of VMs, we have introduced Enhanced minPower and maxUtilization (EMPMU) VM migration policy; and c) efficient utilization of cloud resources and VM placement are achieved using SLA-aware Modified Best Fit Decreasing (MBFD) algorithm. We have validated our test results using CloudSim toolkit 3.0.3. Finally, experimental results have shown better resource utilization, reduced energy consumption and SLA violation in heterogeneous dynamic cloud environment.

• 한국태양에너지학회:학술대회논문집
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• 2011.11a
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• pp.256-263
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• 2011

Recently, curtain wall structure is constructed according to increasing high rise building. Glass is usually used in opening of curtain wall structure and window area ratio is finally increased. Excessive Daylighting and solar radiation by large window area ratio cause discomfort glare and add to cooling load in the case of office that is heavy on lighting and cooling. Therefore, this study suggests to use low transmittance window for solve those problems. Indoor lighting environment and building energy performance were analyzed by increasing transmittance from 10% to 90% and comparing fixed venetian blind. Consequently, the range of transmittance that is possible to daylighting and prevent discomfort glare. Secondary energy consumption is efficient in the case that transmittance is the range of from 20% to 50%, primary energy consumption is nice on from 20% to 40%. If those result put together, the range of window transmittance from 30% to 50% is proper in the office in lighting environment and energy consumption aspects.

• Journal of the Korean Solar Energy Society
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• v.29 no.6
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• pp.39-44
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• 2009

Entering in the time of high oil price, seriousness of an energy effect sector has given a huge impact and the importance of energy is growing. Especially, building energy occupying 24% of total demand of energy is expected to be possible to reduce energy demand more than other section. To reduce the building energy consumption, this study analyzes function and thermal performance of Super window by heat experimental apparatus. Super window is a 2-track low-e glazing window for high insulation efficiency. By applying the results of this experiment to building energy efficience rating tool, this study compares energy efficiency rates depending on a region.-Jeju, South, Central. And it shows how much does Super window reduce Building energy consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2821-2839
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• 2015

Energy consumption by large computing systems has become an important research theme not only because the sources of energy are depleting fast but also due to the environmental concern. Computational grid is a huge distributed computing platform for the applications that require high end computing resources and consume enormous energy to facilitate execution of jobs. The organizations which are offering services for high end computation, are more cautious about energy consumption and taking utmost steps for saving energy. Therefore, this paper proposes a scheduling technique for Minimizing Energy consumption using Adapted Genetic Algorithm (MiE-AGA) for dependent tasks in Computational Grid (CG). In MiE-AGA, fitness function formulation for energy consumption has been mathematically formulated. An adapted genetic algorithm has been developed for minimizing energy consumption with appropriate modifications in each components of original genetic algorithm such as representation of chromosome, crossover, mutation and inversion operations. Pseudo code for MiE-AGA and its components has been developed with appropriate examples. MiE-AGA is simulated using Java based programs integrated with GridSim. Analysis of simulation results in terms of energy consumption, makespan and average utilization of resources clearly reveals that MiE-AGA effectively optimizes energy, makespan and average utilization of resources in CG. Comparative analysis of the optimization performance between MiE-AGA and the state-of-the-arts algorithms: EAMM, HEFT, Min-Min and Max-Min shows the effectiveness of the model.

• Membrane and Water Treatment
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• v.2 no.4
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• pp.239-250
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• 2011

A photovoltaic powered ultrafiltration and reverse osmosis system was tested with a number of natural groundwaters in Australia. The objective of this study was to compare system performance at six remote field locations by assessing the impact of water composition and fluctuating energy on inorganic contaminant removal using a BW30-4040 membrane. Solar irradiance directly affected pressure and flow. Groundwater characteristics (including TDS, salts, heavy metals, and pH), impacted other performance parameters such as retention, specific energy consumption and flux. During continual system operation, retention of ions such as $Ca^{2+}$ and $Mg^{2+}$ was high (> 95%) with each groundwater which can be attributed to steric exclusion. The retention of smaller ions such as $NO_3{^-}$ was affected by weather conditions and groundwater composition, as convection/diffusion dominate retention. When solar irradiance was insufficient or fluctuations too great for system operation, performance deteriorated and retention dropped significantly (< 30% at Ti Tree). Groundwater pH affected flux and retention of smaller ions ($NO_3{^-}$ and $F^-$) because charge repulsion increases with pH. The results highlight variations in system performance (ion retention, flux, specific energy consumption) with real solar irradiance, groundwater composition, and pH conditions.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.11
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• pp.746-751
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• 2008

The best plan to reduce the building energy consumption is that the insulation performance should be improved because the insulation and airtight of building envelopes have an effect on the energy consumption basically. New insulation materials, which have the high performance and are above insulation standard, have been developed steadily. Because there are not studies on the building energy rating system and economic evaluation considering new insulation materials, these matters should be studied. In result alternatives, which applied 6 high performance material each, reduce the annual heating energy and raise the building energy rating. Applying the vacuum insulation material(Case 1, 2) and vacuum or triple glazing can retrieves the investment with $120 and $140$\sim$150 per barrel each.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.50-55
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• 2022

Acceleration performance, maximum velocity, urban driving energy consumption, and high-way driving energy consumption are important characteristics of electric vehicle driving. This study analyzes the effect of a gear ratio on these characteristics for a front wheel drive electric vehicle. The normalized sensitivity metric is used to compare the sensitivity of these scaled characteristics to the changes in the gear ratio. The sensitivity analysis results show that the normalized values are 0.95 for maximum velocity, 0.91 for acceleration performance, 0.51 for urban driving energy consumption, and 0.24 for high-way driving energy consumption. Therefore, the maximum velocity was affected the most by the changes in the gear ratio. These results can be used to determine the gear ratio of a front wheel drive electric vehicle to optimize the driving characteristics simultaneously.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.47 no.1
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• pp.46-58
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• 2011

A steady-state analysis and a simple dynamic model as simplified methods are developed, and results of energy consumption loads are compared with results obtained using computer to evaluate the analytical solution. Before obtaining simplified model a mathematical model is formulated for the effect of wall mass on the thermal performance of four different houses having various wall construction. This analytical study was motivated by the experimental work of Burch et al. An analytical solution of one-dimensional, linear, partial differential equation for wall temperature profiles and room air temperatures is obtained using the Laplace transform method. Typical Meteorological Year data are processed to yield hourly average monthly values. This study is conducted using weather data from four different locations in the United States: Albuquerque, New mexico; Miami, Florida; Santa Maria, California; and Washington D.C. for both winter and summer conditions. The steady state analysis that does not include the effect of thermal mass can provide an accurate estimate of energy consumption in most cases except for houses #2 and #4 in mild weather areas. This result shows that there is an effect of mass on the thermal performance of heavily constructed house in mild weather conditions. The simple dynamic model is applicable for high cycling rates and accurate values of inside wall temperature and ambient air temperature.

• Journal of Korea Foundry Society
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• v.41 no.1
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• pp.16-25
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• 2021

The development of technology to prevent environmental pollutants and reduce energy consumption has already become a very significant issue not only for the foundry industry but also for society as a whole. In this paper, we introduce a new dust collector developed for low energy consumption and high performance compared to a roof top dust collector. The roof top dust collector which is using widely in the domestic foundry plant has a low performance about the dust suction ability in spite of high energy consumption because it is installed in a high place to collect the whole dust from all processes in foundry. A dust collector away from dust sources inevitably has low energy efficiency. The development of an efficient collector for foundry is very difficult because the position of the dust source continues to change from the melting process to the pouring process. New dust collector is installed on the ladle transfer equipment such as cranes, hoists, and monorails to effectively respond to moving dust sources. The movable device, attached close to the source of dust, provides high performance even with low energy consumption. The new dust collector is expected to be an environment-friendly device that can be applied to the foundry.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.175-181
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• 2021

This paper analyzes the artificial intelligence-based approach for short-term energy consumption prediction. In this paper, we employ the reinforcement learning algorithms to improve the limitation of the supervised learning algorithms which usually utilize to the short-term energy consumption prediction technologies. The supervised learning algorithm-based approaches have high complexity because the approaches require contextual information as well as energy consumption data for sufficient performance. We propose a deep reinforcement learning algorithm based on multi-agent to predict energy consumption only with energy consumption data for improving the complexity of data and learning models. The proposed scheme is simulated using public energy consumption data and confirmed the performance. The proposed scheme can predict a similar value to the actual value except for the outlier data.