• Journal of the Korean Solar Energy Society
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• v.33 no.1
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• pp.48-56
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• 2013

Energy consumption analysis of multi-family apartment is an important area of research for the design of energy-saving housing. In this study, we selected a universal type of Flat-type apartments and analyzed the heating energy consumption of variables such as U-value, G-value, infiltration rate, heating setpoint and boiler efficiency with EnergyPlus and eQUEST. With these results, we identify the characteristics of EnergyPlus and eQUEST and provided base data for the design of energy-saving housing. The results indicate that infiltration rate is the most important factors to consider. And eQUEST heating energy consumption is approximately 10% higher compared to the EnergyPlus under same condition.

• International Journal of Railway
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• v.6 no.2
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• pp.33-44
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• 2013

In recent years, energy consumption in the transportation sector by expanding motorization continues to increase in almost every country in the world. Moreover, the growth rate of the transportation energy consumption is significantly higher than those of the civilian and industrial sectors. Therefore, every country strives to reduce its dependence on private transport, which is the main contributor to the transportation energy consumption. In many countries, concepts such as Transit Oriented Development (TOD) or New Urbanism, which controls road traffic by increasing the proportion of the public transportation significantly, have been implemented to encourage a modal shift to public transport. However, the level of change required for eliminating environmental problems is a challenging task. Minimizing transportation energy consumption by controlling the increase of the traffic demand and maintaining the level of urban mobility simultaneously is a pressing dilemma for each city. Grasping the impact of the diversity of the urban transport and infrastructure is very important to improve transportation energy efficiency. However, the potential for reducing urban transportation energy consumption has often been ineffectively demonstrated by the diversity of cities. Therefore, the accuracy of evaluating the current efficiency rate of the urban energy consumption is necessary. Nevertheless, quantitative analyses related to the efficiency of transportation energy consumption are scarce, and the research on the current condition of consumption efficiency based on international quantitative analysis is almost nonexistent. On the basis of this background problem definitions, this research first built a database of the transportation energy consumption of private modes in 119 cities, with an attempt to reflect individual travel behaviors calculated by Person Trip data. Subsequently, Data Envelopment Analysis (DEA) was used as an assessment method to evaluate the efficiency of transportation energy consumption by considering the diversity of the urban traffic features in the world cities. Finally, we clarified the current condition of consumption efficiency by attempting to propose a target values for improving transportation energy consumption.

• Journal of Energy Engineering
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• v.14 no.2 s.42
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• pp.147-152
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• 2005

Calculation equations of fired fuel comsumption rating at boiler can lead from combustion anal-ysis and boiler heat balance using mass & energy conservations. By comparing calculation equation results with those of measurement, we can confirm the deviation of fuel consumption rate, and correction rate, and correction degree, and can also establish the proven technology to apply the equation at the site. We applied fuel rate equation to the operating power plant and recorded $2.4\%\;&\;1.5\%$ of deviation at each coal and oil fired boilers. This range of deviation is regarded as trustable to apply the fuel consumption equation to the actual site.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.12
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• pp.1227-1233
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• 2004

Air handling unit (AHU)'s air filter pressure difference is important for energy consumption and indoor air quality. Both energy Performance data and air filter differential pressure of AHU in real office buildings were monitored and analyzed to investigate quantitatively energy impact as dust buildup level on air filter grows. We also modeled and simulated CAV system using HVACSIM＋ program to examine the energy effect of dust buildup on filters. Through analysis of time series pressure drop data, the filter pressure difference rate has been increased due to cumulative supply air flow rate increase. As filter pressure drop increased to 1 inch water column, it is found that the supply air flow rate was decreased by 10%, the chilled water flow rate was increased by 5.9% and the pump energy consumption was increased to 5.9%.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.13 no.4
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• pp.8-13
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• 2017

The effects of operational conditions of cooling water system on energy consumption for central cooling system are researched by using TRNSYS program. Cooling tower water pump flow rate, cooling tower fan flow rate, and condenser water temperature with various dry-bulb and wet-bulb temperatures are varied and their effects on total and component power consumption are studied. If the fan maximum flow rates of cooling tower is decreased, cooling tower fan and total power consumptions are increased. If the cooling tower water pump maximum flow rates is decreased, chiller and total power consumptions are increased. If condenser water set-point temperature is increased, chiller power consumption is increased and cooling tower fan power consumption is decreased, respectively.

• Korean Journal of Construction Engineering and Management
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• v.16 no.3
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• pp.123-131
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• 2015

There are a number of policies that have been established to reduce greenhouse gases emissions and reduce energy consumption. These polices, however, only reflect the building energy consumption saving rate without considering building energy consumption characteristic. If building that already use less energy apply the same saving rate to reduce energy consumption, it is less effective. Therefore, this study classified building energy consumption characteristics and investigated approaches to adopt individual reduction rates according to energy consumption. Analysis results showed that there are differences in energy consumption depending on building use, and therefore, we classified buildings by use. We also proposed a formula to set a reduction goal for rate of energy consumption according to energy consumption. We verified our approach in a top-end neighborhood facility in Seoul. The energy consumption savings goal of this study can be applied individually, but determining whether a building can reduce energy consumption towards a saving goal requires a closer look at each building.

• International Journal of High-Rise Buildings
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• v.8 no.2
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• pp.101-106
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• 2019

Assessing the energy performance of supertall buildings often does not consider variations in energy consumption due to the change of environmental conditions such as temperature, pressure, and wind speed associated with differing elevations. Some modelers account for these changing conditions by using a conventional temperature lapse rate, but not many studies confirm to the appropriateness of applying it to tall buildings. This paper presents and discusses simulated annual energy consumption results from a 600 m tall skyscraper floor plate located in Dubai, UAE, assessed using ground level weather data, a conventional temperature lapse rate of $6.5^{\circ}C/km$, and more accurate simulated 600 m weather data. A typical office floorplate, with ASHRAE 90.1-2010 standards and systems applied, was evaluated using the EnergyPlus engine through the OpenStudio graphical user interface. The results presented in this paper indicate that by using ground level weather data, energy consumption at the top of the building can be overestimated by upwards of 4%. Furthermore, by only using a lapse rate, heating energy is overestimated by up to 96% due to local weather phenomenon such as temperature inversion, which can only be conveyed using simulated weather data. In addition, sizing and energy consumption of fans, which are dependent both on wind and atmospheric pressure, are not accurately captured using a temperature lapse rate. These results show that that it is important, with the ever increasing construction of supertall buildings, to be able to account for variations in climatic conditions along the height of the building. Adequately modeling these conditions using simulated weather data will help designers and engineers correctly size mechanical systems, potentially decreasing overall building energy consumption, and ensuring that these systems are able to provide the necessary indoor conditions to maintain occupant comfort levels.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.3
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• pp.90-96
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• 2004

The objective of this study was to develop a model for safe work load based on a physiological model of metabolic energy of manual material handling tasks. Fifteen male subjects voluntarily participated in this study. Lifting activities with four different weights, 0, 8, 16, 24kg, and four different working frequencies (2, 5, 8, 11 lifts/min) for a lifting range from floor to the knuckle height of 76cm were considered. Oxygen consumption rates and heart rates were measured during the performance of sixteen different lifting activities. Simplified predictive equations for estimating the oxygen consumption rate and the heart rate were developed. The oxygen consumption rate and the heart rate could be expressed as a function of task variables; frequency and the weight of the load, and a personal variable, body weight, and their interactions. The coefficients of determination ($r^2$) of the model were 0.9777 and 0.9784, respectively, for the oxygen consumption rate and the heart rate. The model of oxygen consumption rate was modified to estimate the work load for the given oxygen consumption rate. The overall absolute percent errors of the validation of this equation for work load with the original data set was 39.03%. The overall absolute percent errors were much larger than this for the two models based on the US population. The models for the oxygen consumption rate and for the work load developed in this study work better than the two models based on the US population. However, without considering the biomechanical approach, the developed model for the work load and the two US models are not recommended to estimate the work loads for low frequent lifting activities.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.188-194
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• 2012

Cognitive networks (CNs) are capable of enabling dynamic spectrum allocation, and thus constitute a promising technology for future wireless communication. Whereas, the implementation of CN will lead to the requirement of an increased energy-arrival rate, which is a significant parameter in energy harvesting design of a cognitive user (CU) device. A well-designed spectrum-sensing scheme will lower the energy-arrival rate that is required and enable CNs to self-sustain, which will also help alleviate global warming. In this paper, spectrum sensing in a multi-user cognitive ad hoc network with a wide-band spectrum is considered. Based on the prospective spectrum sensing, we classify CN operation into two modes: Distributed and centralized. In a distributed network, each CU conducts spectrum sensing for its own data transmission, while in a centralized network, there is only one cognitive cluster header which performs spectrum sensing and broadcasts its sensing results to other CUs. Thus, a wide-band spectrum that is divided into multiple sub-channels can be sensed simultaneously in a distributed manner or sequentially in a centralized manner. We consider the energy consumption for spectrum sensing only of an analog-to-digital convertor (ADC). By formulating energy consumption for spectrum sensing in terms of the sub-channel sampling rate and whole-band sensing time, the sampling rate and whole-band sensing time that are optimal for minimizing the total energy consumption within sensing reliability constraints are obtained. A power dissipation model of an ADC, which plays an important role in formulating the energy efficiency problem, is presented. Using AD9051 as an ADC example, our numerical results show that the optimal sensing parameters will achieve a reduction in the energy-arrival rate of up to 97.7% and 50% in a distributed and a centralized network, respectively, when comparing the optimal and worst-case energy consumption for given system settings.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.535-545
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• 2020

This study aims to conserve and monitor energy use in public sewage treatment plants by utilizing data from the SCADA system and by controlling the aeration rate required for maintaining effluent water quality. Power consumption in the sewage treatment process was predicted using the equipment's uptime, efficiency, and inherent power consumption. The predicted energy consumption was calibrated by measured data. Additionally, energy efficiency indicators were proposed based on statistical data for energy use, capacity, and effluent quality. In one case study, a sewage treatment plant operated via the SBR process used ~30% of energy consumed in maintaining the bioreactors and treated water tanks (included decanting pump and cleaning systems). Energy consumption analysis with the K-ECO Tool-kit was conducted for unit processing. The results showed that about 58.7% of total energy consumed was used in the preliminary and biological treatment rotating equipment such as the blower and pump. In addition, the energy consumption rate was higher to the order of 19.2% in the phosphorus removal process, 16.0% during sludge treatment, and 6.1% during disinfection and discharge. In terms of equipment energy usage, feeding and decanting pumps accounted for 40% of total energy consumed following 27% for blowers. By controlling the aeration rate based on the proposed feedback control system, the DO concentration was reduced by 56% compared pre-controls and the aeration amount decreased by 28%. The overall power consumption of the plant was reduced by 6% via aeration control.