• KIEAE Journal
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• v.12 no.3
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• pp.101-106
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• 2012

Lighting energy accounts for approximately 20% of the electrical energy used worldwide. Thus, High efficiency Light emitting diode(LED)lighting is getting more popular as the next generation lighting replaced to traditional lighting fixtures. Also, LED lighting not only has a long lifetime but also can realize a variety visual environments through the wavelengh control. The lighting energy varies depending on the Spectral Power Distribution(SPD) even though the Illuminance level is same. Therefore, This study indicates that the difference of indoor energy consumption under the same illuminance level when Spectral Power Distribution(SPD) is different. As a result, Lighting energy consumption under red-color emphasizing SPD is about 10% lower than under blue-color emphasizing SPDs.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.613-624
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• 2021

This paper analyzes the relationship between income distribution and energy consumption from a Pareto optimal approach. For this purpose, the causality relationship between electricity consumption per capita (kWh) with respect to country groups and energy consumption per capita (kg of oil equivalent) along with gross domestic product per capita was analyzed. In addition to this purpose, a Pareto analysis was conducted to determine the countries with the highest per capita national income, how much of the world total energy they consume, and whether the law of power in the energy and electricity markets exists. Finally, the impact of official development assistance provided to low-income countries by high-income countries on the low-income countries' electricity and energy consumption was analyzed. In other words, it was questioned whether pareto redistribution policies serve the purpose or not. The Engle-Granger causality approach was used in the analysis of the causality relationship between variables. Our analysis indicated that, first, the energy data of the country groups may be inadequate in revealing income inequalities. Second, the existence of Pareto law of power and global income inequality can be explained based on energy data. Finally, Pareto optimal redistribution policies to eliminate income inequality remain inadequate in practice.

• Current Photovoltaic Research
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• v.11 no.4
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• pp.134-143
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• 2023

Efforts are being made to respond to global warming. Interest in and demand for the private sector-led RE100 campaign is also increasing. Self-built solar power generation, one of the implementation tools for RE100, is not expanding. However, it can be an economical means of implementation in the long run. In this study, we intend to analyze the impact on the optimal ratio of self-solar power generation using HOMER simulation. OPR defines the optimal solar power generation ratio and looks into what changes there are in the optimal solar power ratio when self-power consumption increases and external power purchase price changes. As a result, the optimal rate of self-solar power generation has a low impact even if self-power consumption increases. As the external power unit price increases, the optimal ratio increases, and at a power unit price of 100 KRW/kWh, OPR is 24%; at 200 KRW/kWh OPR is 31%; and at 300 KRW/kWh OPR is 34%. This shows that the electricity price replaced during the life cycle has a high impact on the economic feasibility of solar power generation. However, when the external power unit price reached a certain level, the increase in OPR decreased. This shows that it is difficult for domestic companies to achieve RE100 based on the economic feasibility of solar energy alone. Therefore, efforts are needed to supply renewable energy in the public sector.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.2
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• pp.61-68
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• 2020

Nuclear power plants have a lower cost of power generation, and they are more eco-friendly than other power generation plants. Also, we need to prepare nuclear plant accidents because of their severe damage. In the event of a safety accident, such as a radiation leak, by applying a wireless sensor network to a nuclear power plant, many sensor nodes can be used to monitor radiation and transmit information to an external base station to appropriately respond to the accident. However, applying a wireless sensor network to nuclear power plants requires routing protocols that consider the sensor network size and bypass obstacles such as plant buildings. In general, the hierarchical-based routing protocols are efficient in energy consumption. In this study, we look into the problems that may occur if hierarchical-based routing protocols are applied to nuclear power plants and propose improved routing protocols to solve these problems. Simulation results show that the proposed routing protocol is more effective in energy consumption than the existing LEACH protocol.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.300-313
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• 2014

Various Time Synchronization protocols for a Wireless Sensor Network (WSN) have been developed since time synchronization is important in many time-critical WSN applications. Aside from synchronization accuracy, energy constraint should also be considered seriously for time synchronization protocols in WSNs, which typically have limited power environments. This paper performs analysis of prominent WSN time synchronization protocols in terms of power consumption and test by simulation. In the analysis and simulation tests, each protocol shows different performance in terms of power consumption. This result is helpful in choosing or developing an appropriate time synchronization protocol that meets the requirements of synchronization accuracy and power consumption (or network lifetime) for a specific WSN application.

• Journal of the Korean Institute of Educational Facilities
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• v.18 no.5
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• pp.13-21
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• 2011

In case of school buildings, energy consumption has been noticeably on the increase, along with the changes in outdoor temperature triggered by the improvement in national economic development and educational environments. Research on the characteristics of energy consumption in school buildings influenced by the changes in outdoor temperature is considered very significant in social aspects in that it will be fundamental to the suggestion of the alternatives, such as saving energy consumption in construction buildings and control of emitting carbon dioxide. In this regard, this study examined sensitivity to temperature of power consumption in school buildings, based on the changes of outdoor temperature for the past five years in the target buildings of elementary, middle and high schools and the amount of energy consumption. From the results, it has been believed that this study was very significant in terms of figuring out a quantitative, optimum level of energy consumption, maintenance of pleasant environments and functions, and the necessity of effective energy use and management in school buildings.

• 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.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.11
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• pp.605-611
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• 2017

The purpose of this study is to calculate the energy consumption rate based on data regarding energy use in office buildings, and to confirm the general characteristics of energy consumption. The energy consumption rate of the building is calculated by dividing the energy consumption by the floor area. The energy consumption rate of small-sized office buildings was calculated as $101.48{\sim}201.55kWh/m^2{\cdot}year$ and in the case of medium-sized buildings, the range was $92.77{\sim}177.89kWh/m^2{\cdot}year$. In the case of small buildings, it was found that the energy consumption was $73.24kWh/m^2{\cdot}year$ in electronic device, $34.31kWh/m^2{\cdot}year$ in hot water supply, and $18.37kWh/m^2{\cdot}year$ in heating. In the case of medium-sized buildings, electronic devices was $73.08kWh/m^2{\cdot}year$, lighting was $18.35kWh/m^2{\cdot}year$ and heating, $15.37kWh/m^2{\cdot}year$. In all of the study buildings, the peak heating energy use was observed from 8:00 a.m. to 10:00 a.m during the winter, and the peak power management was required. Energy use at and around the midnight hour is confirmed to be 40~60% of weekly working hours, so it is necessary to manage power use at night time as well as during the day. In order to improve the accuracy of future studies, it is necessary to make efforts to secure the data with standardized energy measuring units for the various type of buildings.

• Journal of Drive and Control
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• v.17 no.2
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• pp.38-44
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• 2020

Various efforts have been initiated to reduce the energy consumption of the compressor as it is one of the approaches to saving a large portion of the fixed cost of the production site. Various results of reducing the energy consumption of the compressor have been reported, but to reduce the energy consumption of the compressors fundamentally, regular management of the compressor should ensure optimum operation. This requires periodic on-site visits by experts, but is often overlooked as a cost issue, resulting in the use of the compressor in low-efficiency conditions. Thus, it is necessary to develop a low-cost evaluation technology for compressor condition monitoring and efficiency analysis to ensure that the compressor is always driven at the optimum efficiency without imposing undue burden on the compressor user. In this study, a sensor was installed at the inlet, outlet, and power supply of the compressor, and a method for evaluating the energy consumption of the compressor using the minimum sensor was derived. The experimental results are presented to show the validity of the proposed method. It was confirmed that the energy consumption of the compressor can be easily as well as efficiently evaluated by using the method developed in this study.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.871-880
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• 2009

Along with the complexity and size growth of embedded software, it is critical to meet the nonfunctional requirements such as power consumption as well as functional requirements such as correctness. This paper, apart from the existing studies of source code-based power analysis, proposes an approach of model-based power analysis using UML 2.0. Specially, we focus on the development of energy library to analyze the power consumption of embedded software. Our energy library supports model-based power analysis, and also supports the easy adaption for the change of embedded application.