• Journal of Energy Engineering
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• v.23 no.4
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• pp.61-72
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• 2014

This paper analyzed transition pathways toward a low carbon society in Korea to meet global $2^{\circ}C$ climate target. Lower economic growth, industrial structure change, enhance of energy demand management, decarbonization of power sector, and replacement of low carbon fuel could reduce greenhouse gas (GHG) emission from fuel combustion in 2050 by 67% against in 2011, or by 74% against in BAU (Business-As-Usual). Lower economic growth contributes to 13% of cumulative emission reduction relative to BAU, industrial structure change 9%, enhance of energy demand management 72%, decarbonization of power sector 5% and replacement of low carbon fuel 1% respectively. Final energy consumption in 2050 needs to be reduced to 50% relative to 2011, or to 41% relative to BAU. Nuclear, coal and renewable energy represent 31%, 40%, 2% respectively among electricity generation in 2011, but 38%, 2%, 32% in 2050. CCS represents 23% of total generation in 2050. Emission intensity of electricity in 2050 was decreased to 19% relative to 2011, or to 24% relative to BAU. Primary energy in 2050 was decreased to 64% compared to 2011, or to 44% compared to BAU. Final energy consumption, primary energy supply and GHG emission from fuel combustion from 1990 to 2011 increased by 176%, 197%, 146%. Radical change from historical trend is required to transit toward a low carbon society by 2050. Appropriate economic growth, structural change to non-energy intensive industries, energy technology research, development and deployment (RD&D) in terms of enhancement of energy efficiency and low carbon energy supply technologies, and fuel change to electricity and renewable energy are key instruments.

• Environmental and Resource Economics Review
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• v.24 no.1
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• pp.141-164
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• 2015

The concept of consumption-based greenhouse gas (GHG) inventory is directly related with the carbon content of international trade. Along the lines of the consumption-based GHG inventory, we investigate domestic and foreign carbon contents embodied in sectoral exports of Korea. In addition to the analysis of carbon content of exports, it is investigated how much share of responsibility for carbon emissions of Korea belongs to each major trading partner of Korea. We also compute the carbon intensities of Korean exports in carbon chain with other trading partners and find some characteristics revealed in Korea's carbon emissions embodied in its exports.

• Journal of Internet of Things and Convergence
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• v.6 no.2
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• pp.11-18
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• 2020

Since the end devices of the Internet of Things (IoT) are battery operated products, careful consideration for ultra-low power (ULP) is required. The Micro Controller Unit (MCU) industry has developed very effective functions to save energy, but developers have difficulty in selecting the MCU because various operating modes are applied to reduce energy consumption by manufacturers. Therefore, this paper introduces ULPMark benchmark, a standardized benchmark method that can compare MCUs of various vendors and feature sets, and provides hardware functions for ultra-low-power operation of the two platforms that received the high evaluation scores from ULPMark. In addition, we investigated and analyzed how developers can utilize the functions for ultra low power consumption through driver APIs and detailed register control.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.17-25
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• 2023

As the range of use of urban unmanned aerial vehicles (UAV) expands, it is necessary to operate UAVs efficiently because of its limited battery capacity. For this, it is required to find the optimal flight profile with various simulations. Therefore, it is important to predict the power and energy consumption of the UAV battery. In this paper, we analyzed the relationship between the speed and acceleration of the UAV and power consumption during the flight. Then, we derived a linear model, which is easily utilized. In addition, we also derived an accurate power consumption model based on deep neural network learning. To find the efficient model, we used learning data as 1) the GPS 3-axis velocity and acceleration data, 2) the IMU 3-axis velocity only, and 3) the IMU 3-axis velocity and acceleration data. The final model shows 5.86% error rate for power consumption and 1.50% error rate for the cumulative energy consumption.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1141-1154
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• 2015

This paper describes the convergence of the energy technology and information and communication technology (ICT), which helps to consume less energy effectively. While a lot of researches have done against the increase of world energy usage, most of them focus on the efficiency of energy supply, transfer, and consumption equipment. Applying the ICT to decrease energy usage could help to find energy saving factors in the new field that has not been considered as a valuable one before. The big data service with the energy technology and ICT convergence enables correlation analyses of large sets of energy and environmental data. Finding a data tendency with a big data service helps to develop energy saving policies. Furthermore, it could make a further step to develop a new business model. This paper introduces the real cases of the company and project that provides a big data service with the ICT convergence.

• Environmental and Resource Economics Review
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• v.21 no.2
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• pp.271-299
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• 2012

The relationship between environment and economic growth has been controversial for a long time. The cores of controversy are endogeneity problem and omitted variable bias. This paper tests EKC (Environmental Kuznets Curves) hypothesis by considering econometric issues and estimates the effects of energy mix on $CO_2$ emissions empirically and tests with time series during 1981~2008. By the results of this analysis, we convince EKC Hypothesis which the relationship between $CO_2$ emissions and economic growth is the inverted U-shaped and the national energy mix contributes significantly to GHG mitigation. We also find that the nuclear energy has the greatest contribution for $CO_2$ mitigation and the renewable energy does not seem to contribute little to the $CO_2$ mitigation because the proportion of renewable energy in Korea is negligible. In terms of final energy consumption, $CO_2$ increases and transportation sector is statistically and significantly associated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2091-2098
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• 2006

In this paper, it proposes a protocol of resource adaptive data dissemination for sensor nodes in a wireless sensor network. In general, each sensor node used in a wireless sensor network delivers the required information to the final destination by conducting cooperative works such as sensing, processing, and communicating each other using the battery power of a independent sensor node. So, a protocol used for transferring the acquired information to users through the wireless sensor network can minimize the power consumption of energy resource given to a sensor node. Especially, it is very important to minimize the total amount of power consumption with a method for handling the problems on implosion. data delivery overlapping, and excessive message transfer caused by message broadcasting. In this paper, for the maintaining of the shortest path between sensor nodes, maximizing of the life time of a sensor node and minimizing of communication cost, it presents a method for selecting the representative transfer node for an event arising area based on the negotiation scheme and maintaining optimal transfer path using hop and energy information. Finally, for the performance evaluation, we compare the proposed protocol to existing directed diffusion and SPIN protocol. And, with the simulation results, we show that the proposed protocol enhances the performance on the power consumption rate when the number of overall sensor nodes in a sensor network or neighbor sensor nodes in an event area are increased and on the number of messages disseminated from a sensor node.

• Journal of Digital Convergence
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• v.9 no.2
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• pp.141-152
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• 2011

The data center has become an increasingly important part of most business operations. An increasing demand for computation has led to increasing industry energy consumption. Therefore, higher-than-normal rates of energy efficiency have become a core issue in the life cycle of data center. In this paper, we proposed the framework of level diagnosis for green data centre that can be used to diagnose the levels of capability maturity model. This framework contains the 5 key areas such as construction, air-conditioning, electricity, information technology, organization and indicators that can be applied as basic level diagnosis guide for green data center.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.447-449
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• 2021

Various wireless sensor network protocols have been proposed to maintain the network for a long time by minimizing energy consumption. Using the K-means clustering algorithm takes longer to cluster than traditional hierarchical algorithms because the center point must be moved repeatedly until the final cluster is established. For K-means clustering-based protocols, only the residual energy of nodes or nodes near the center point of the cluster is considered when the cluster head is elected. In this paper, we propose a new wireless sensor network protocol based on K-means clustering to improve the energy efficiency while improving the aforementioned problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.403-411
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• 2014

In this paper, an algorithm of extracting the features of home appliances and automatically building a database to identify home appliances is designed and presented. For the verification, a software library supporting this algorithm is implemented and added to an power management system server, which was already implemented to support real-time monitoring of home appliances' power consumption status and controlling their power. The implemented system consists of a system server and clients, each of which measures the power consumed by a home appliance plugged in it and transmits the information to the server in real-time over a wireless network. Through experiments, it is verified that it is possible to identify any home appliance connected to a specific client.