• International conference on construction engineering and project management
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• 2015.10a
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• pp.706-707
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• 2015

Our country is aiming at 30% reductions in building energy consumption accounting for 39% of the total energy consumption by 2020[1]. For this purpose, the government is developing and applying the Building Energy Management System (hereinafter, referred to as "BEMS", Smart plug, etc.) while the researches on new renewable energy development. BEMS, which is applied with focus on large buildings, is inducing energy management of the entire building through energy measurement and data management, but considering its economic efficiency, it's very difficult to apply BEMS to small & medium-size buildings. Hereupon, this study intends to implement the case analysis of deterioration and economic efficiency of major equipment in buildings on the basis of electricity consumption which has been measured targeting small & medium-size buildings for a certain period by taking into account that equipment deterioration is a contributor to the increase in energy consumption.

• Electronics and Telecommunications Trends
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• v.39 no.4
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• pp.32-41
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• 2024

Building energy management plays a crucial role in improving energy efficiency and optimizing energy usage. To achieve this, it is important to monitor and analyze energy-related data from buildings in real time using sensors to understand energy consumption patterns and establish optimal operational strategies. Because of the uncertainties in building energy-related data, there are challenges in analyzing these data and formulating operational strategies based on them. Artificial intelligence (AI) technology can help overcome these challenges. This paper investigates past and current research trends in AI technology and examines its future prospects for building energy management. By performing prediction and analysis based on energy consumption or supply data, the future energy demands of buildings can be forecasted and energy consumption can be optimized. Additionally, data related to the surrounding environment, occupancy, and other building energy-related factors can be collected and analyzed using sensors to establish operational strategies aimed at further reducing energy consumption and increasing efficiency. These technologies will contribute to cost savings and help minimize environmental impacts for building owners and operators, ultimately facilitating sustainable building operations.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.4
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• pp.475-483
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• 1999

A lab-scale test was carried out to study the reduction of electrical energy consumption in the pulsed corona discharge process for nitrogen oxides removal. The experiment was mainly focused on 1) the activation of pollution removal reactions by chemical additives and 2) the optimization of electrical circuit for the efficient energy transfer from the power supply to the corona reactor. Hydrocarbon chemical additives used in the experiment are thought to be responsible for the enhancement of the NO conversion through the chain reactions of free radicals such as, R, RCO, and RO. Electrical energy consumption per converted NO molecule has a minimum value of 17 eV when pentanol is injected. When ethylene and propylene are injected, 30 eV and 22 eV of electrical energy consumption is required for the conversion of NO molecule respectively. The ratio of the pulse forming capacitance$(C_e)$ to the reactor capacitance$(C_R)$ plays an important role in the energy transfer efficiency to the reactor. Maximum energy transfer efficiency of approximately 72% could be obtained by using the pulse forming capacitance which is 3.4 times larger than the reactor capacitance, and also the maximum NO conversion efficiency was observed with the same condition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2302-2324
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• 2014

Cluster-based wireless sensor network (WSN) can significantly reduce the energy consumption by data aggregation and has been widely used in WSN applications. However, due to the intrinsic many-to-one traffic pattern in WSN, the network lifetime is generally deteriorated by the unbalanced energy consumption in a cluster-based WSN. Therefore, energy efficiency and network lifetime improvement are two crucial and challenging issues in cluster-based WSNs. In this paper, we propose a Non-Uniform Node Distribution (NUND) scheme to improve the energy efficiency and network lifetime in cluster-based WSNs. Specifically, we first propose an analytic model to analyze the energy consumption and the network lifetime of the cluster-based WSNs. Based on the analysis results, we propose a node distribution algorithm to maximize the network lifetime with a fixed number of sensor nodes in cluster-based WSNs. Extensive simulations demonstrate that the theoretical analysis results determined by the proposed analytic model are consistent with the simulation results, and the NUND can significantly improve the energy efficiency and network lifetime.

• Journal of Climate Change Research
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• v.7 no.2
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• pp.177-184
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• 2016

Recently, the need for technology development of commercial vehicle fuel consumption has emerged. Fuel economy improvement of transport equipment and transportation efficiency, and increasing attention to the logistics cost reduction measures. Increasing attention to the logistics cost reduction measures by fuel economy improvement of transport equipment and transportation efficiency. In this study, we have installed aerodynamic reduction device (side skirt, boat tail) to 14.5 ton cargo trucks and 45 ft tractor-trailers. And the fuel consumption was compared installed before and after. Fuel economy assessment for the aerodynamic reduction value device was tested by modifying the SAE J1321 Joint TMC/SAE Fuel Consumption Test Procedure - Type II test in according domestic situation. Greenhouse gas reductions were calculated in accordance with the scenario, including fuel consumption test results. When the 14.5 ton cargo trucks has been equipped with side skirts and boat tail, it confirmed the improvement in fuel efficiency of 4.72%. One Heavy-duty truck's the annual greenhouse gas reductions value are $6.86ton\;CO_2\;eq$. And if applying the technology to more than 50% of registered 15 ton trucks, greenhouse gas reductions are calculated as $686,826ton\;CO_2\;eq./yr$.

• Journal of ILASS-Korea
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• v.27 no.4
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• pp.195-202
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• 2022

Recently, the global automobile market is rapidly changing from internal combustion engine vehicles to eco-friendly vehicles including electric vehicles. Among eco-friendly vehicles, LPG vehicles are low in fine dust and are suggested as a realistic way to replace diesel vehicles. In addition, it is more economical than gasoline in its class, showing a cost-saving effect. In Korea, the business of converting gasoline into LPG is active. Research is being conducted to apply this to hybrid vehicles. In this study, the difference in energy consumption efficiency was analyzed when LPG fuel was applied by selecting a 2-liter GDI hybrid electric vehicle. The operation of the hybrid system according to various driving characteristics was confirmed by selecting the WLTC mode. As a result, it was confirmed that the BSFC was about 5% lower than that of gasoline fuel when using LPG fuel. This is due to the active operation of the motor while driving. Optimization is required as battery consumption increases from an energy perspective.

• Journal of Platform Technology
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• v.11 no.1
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• pp.3-10
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• 2023

Unmanned Aerial Vehicles (UAVs) have gained significant attention in 5G and 6G wireless networks due to their high flexibility and low hardware costs. However, UAV communication is still challenged by blockage and energy consumption issues. Reconfigurable Intelligent Surfaces (RISs) have emerged as a promising solution to these challenges, enabling improved spectral efficiency and reduced energy consumption by transmitting signals to users who cannot receive signals because of the obstacles. Many previous studies have focused on minimizing power consumption and data transmission delay through phase shift and power optimization. This paper proposes an algorithm that maximizes the sum rate by including bandwidth optimization. Simulation results demonstrate the effectiveness of the proposed algorithm.

• Journal of the Korean Society of Combustion
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• v.22 no.4
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• pp.51-56
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• 2017

The decomposition of tetrafluoromethane has been investigated with the reaction mechanism proposed for freely propagating $CH_4/CF_4/O_2/N_2$ premixed flames on the oxygen enrichment. The factors affecting on the removal efficiency of tetrafluoromethane were analyzed. The increase in flame temperature due to oxygen enrichment has a great influence on the removal efficiency of tetrafluoromethane. At the same oxygen enrichment condition, the removal efficiency in the rich flame is higher than one in the lean flame. The increase of the F/H ratio leads to decrease the flame temperature and the removal efficiency of tetrafluoromethan is decreased at the flame temperature of 2600 K or lower, The elementary reactions that dominate the consumption of tetrafluoromethane are (R1) $CF_4+M=CF_3+F+M$ and (R2) $CF_4+H=CF_3+HF$. (R1) has the greatest effect on the consumption of tetrafluoromethane under the oxygen enhanced flames.

• ETRI Journal
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• v.33 no.3
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• pp.299-309
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• 2011

Energy consumption is a key issue in body sensor networks (BSNs) since energy-constrained sensors monitor the vital signs of human beings in healthcare applications. In this paper, packet size optimization for BSNs has been analyzed to improve the efficiency of energy consumption. Existing studies on packet size optimization in wireless sensor networks cannot be applied to BSNs because the different operational characteristics of nodes and the channel effects of in-body and on-body propagation cannot be captured. In this paper, automatic repeat request (ARQ), forward error correction (FEC) block codes, and FEC convolutional codes have been analyzed regarding their energy efficiency. The hop-length extension technique has been applied to improve this metric with FEC block codes. The theoretical analysis and the numerical evaluations reveal that exploiting FEC schemes improves the energy efficiency, increases the optimal payload packet size, and extends the hop length for all scenarios for in-body and on-body propagation.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.79-90
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• 2019

Maximizing energy efficiency minimizes the energy consumption of computation, storage and communications required for IT services, resulting in economic and environmental benefits. Recent advancement of flash and next generation non-volatile memory technology and price decrease of those memories have led to the rise of so-called AFA (All-Flash Array) storage devices made of flash or next generation non-volatile memory. Currently, the AFA devices are rapidly replacing traditional storages in the high-performance servers due to their fast input/output characteristics. However, it is not well known how effective the energy efficiency of the AFA devices in the real world. This paper shows input/output performance and power consumption of the AFA devices measured on the Linux XFS file system via experiments and discusses energy efficiency of the AFA devices in the real world.