• Journal of the Korean Regional Science Association
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• v.33 no.1
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• pp.3-16
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• 2017

This paper analyzed 16 regional total factor energy efficiency (TFEE) of the Korean manufacturing sector using data envelopment analysis method for the period of 2005-2013. According to the empirical results, it is necessary to use TFEE as well as partial energy efficiency defined by the ratio of energy usage to output (energy intensity) when we compare energy efficiency. Secondly, TFEE in the Korean manufacturing sector is quite different across 16 regions. For example, Gangwon province should improve energy efficiency by 55% compared to Seoul, Gwangju, Ulsan, and Gyeongbuk which are located on production frontier. Furthermore, the estimation of panel tobit regression model showed that the higher non fossil fuel using, the higher production share of large-sized firms, the lower energy intensity, and the lower capital-labor ratio could have positive effect on TFEE.

• The Journal of Sustainable Design and Educational Environment Research
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• v.9 no.2
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• pp.30-37
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• 2010

This study purposed realization and a phase reduction of school building $CO_2$ emissions. Accordingly selected standard school buildings and evaluated life cycle environmental load($CO_2$). This study proposed Green building technology which separated design sector, energy sector, afforestation sector for carbon-neutral city school buildings realization of M-city. As a result, elementary, middle and high schools of M-city built in the year 2013 were required that design sector was Energy Performance Index(EPI) 75 point and energy sector was solar installations more than 25% of the power usage, Solar systems installed more than 10% of total gas consumption and the area of afforesting more than 35% of the ecological area to achieve 30% $CO_2$ reduction compared to the Respectively standard school buildings.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.423-424
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• 2016

Recently, the mass production of Energy storage system (ESS) is actively perform around world. Energy storage system is a technique that stores power to energy storage device to supply energy into grid and load at peak-load. Therefore, the efficient energy management is available by using ESS system. The life of Lithium-ion battery is varied corresponding to the power usage, especially selected depth of discharge (DOD). The lifetime of battery is the one of the most issue of the ESS system because of its stability and reliability. Therefore, lifetime management of battery and power converter of ESS module is required. In this paper, the battery lifetime management method estimating residual power and lifetime of lithium ion battery of ESS system is proposed. Also, total avenue prediction of ESS system is simulated considering the total lifetime of battery.

• Journal of the Korean Solar Energy Society
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• v.31 no.5
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• pp.126-133
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• 2011

The current world wide interest in environmental issues has moved from energy conservation to $CO_2$emission reduction. Recently, according to the increase in demand for water resources, insufficient potable water circumstance is supposed, unless there are corresponding in crease in water conservation and water recycling. This study has attempted to analyze $CO_2$emission reduction by water saving strategies like installation water saving devices, rain water harvesting and grey water system. To do this, this research investigates applicable water conservative strategies by literature review and calculated total water saving. The results show that (1) firstly, the water usage and $CO_2$ emission could be reduced up to 44%, (2) $CO_2$ emission reduction by water saving devices and rainwater harvesting system is about 47.7%, and (3) water usage and $CO_2$ emission reduction by grey water system is about 66%. In the future, this paper will be utilized for water management from the early design stage to maintenance stage of water glutton building.

• Smart Media Journal
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• v.4 no.1
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• pp.25-32
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• 2015

Powering wireless sensors with energy harvested from the environment is coming of age due to the increasing power densities of both storage and harvesting devices and the electronics performing energy efficient energy conversion. In order to maximize the functionality of the wireless sensor network, minimize missing packets, minimize latency and prevent the waste of energy, problems like congestion and inefficient energy usage must be addressed. Many sleep-awake protocols and efficient message priority techniques have been developed to properly manage the energy of the nodes and to minimize congestion. For a WSN that is operating in a strictly energy constrained environment, an energy-efficient transmission strategy is necessary. In this paper, we present a novel transmission priority decision scheme for a heterogeneous body sensor network composed of normal nodes and an energy harvesting node that acts as a cluster head. The energy harvesting node's decision whether or not to clear a normal node for sending is based on a set of metrics which includes the energy harvesting node's remaining energy, the total harvested energy, the type of message in a normal node's queue and finally, the implementation context of the wireless sensor network.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.8
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• pp.394-400
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• 2014

Several models and methods have been developed to verify the improvement of energy performance in retrofit buildings. The verification is important to confirm the effectiveness of new technologies or retrofits. Inverse model toolkit proposed by ASHRAE evaluates the changes of the energy performance of retrofit buildings by using actual energy consumption data. In this study, the inverse model toolkit was used to analyze heating and cooling energy performance of an office building. Analyzed coefficients of correlation of actual energy consumption with estimated energy consumption was above 0.92 and well fitted. It was confirmed that energy consumption of natural gas decreased by 43.4% and also that electricity decreased by 13.8%, after the retrofit of the case building. For the energy usage, cooling energy was increased by 7.4%, heating energy was decreased by 42.3%, hot water and cooking were increased by 3.4%, lighting and electronics were decreased by 19.3%, and the total energy was decreased by 18.9%.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.176-183
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• 2009

Distributed generation(DG) of combined cooling, heat, and power(CCHP)has been gaining momentum in recent year as efficient, secure alternative for meeting increasing energy demands. This paper presents the energy performance of microturbine CCHP system equipped with an absorption chiller by modelling it in hospital building. The orders of study were as following. 1)The list and schedule of energy consumption equipment in hospital were examined such as heating and cooling machine, light etc. 2) Annual report of energy usage and monitoring data were examined as heating, cooling, DHW, lighting, etc. 3) The weather data in 2007 was used for simulation and was arranged by meteorological office data in Daejeon. 4) Reference simulation model was built by comparison of real energy consumption and simulation result by TRNSYS and ESP-r. The energy consumption pattern of building were analyzed by simulation model and energy reduction rate were calculated over the cogeneration. As a result of this study, power generation efficiency of turbine was about 30[%] after installing micro gas turbine and lighting energy as well as total electricity consumption can be reduced by 40[%]. If electricity energy and waste heat in turbine are used, 56[%] of heating energy and 67[%] of cooling energy can be reduced respectively, and total system efficiency can be increased up to 70[%].

• Journal of the Korean Society for Precision Engineering
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• v.30 no.5
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• pp.480-485
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• 2013

Enhancing energy efficiency of machine tools causes substantial impacts on the manufacturing industries, to cope with the competitive introduction of the total energy management strategies. Real-time energy monitoring is essential to identify energy consumption patterns of the machine tools and correlate them with the energy management strategy. Integrated analysis of machine tool's operation status and the corresponding energy usage is most important to accurately evaluate the energy efficiency under the various machining process environments. This paper proposes a system architecture to realize the online energy monitoring system and the embedded energy monitoring approach interconnected with the CNC kernel. The shop-floor operation management system is presented to integrate the proposed online energy monitoring approach.

• International Journal of Air-Conditioning and Refrigeration
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• v.17 no.1
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• pp.15-24
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• 2009

The energy usage and the economical feasibility of the typical two story office building in the three urban locations of South Korea are evaluated as the eight orientations. The smallest energy consume is shown at the true south. The ranges of the low energy consume are $-3l5^{\circ}{\sim}0^{\circ}\;and\;-135^{\circ}{\sim}-180^{\circ}$. There are obvious advantages of passive solar designs such as using a fully glazed facade at the true south in the building. The General Low voltage plan is the effective way for the office building when does not required the high voltage electricity. The energy cost of KEPCO is compared to that of XCEL ENERGY. The portion of the customer charge of XCEL ENERGY is about 10% but it is about 50% of the total tariff of KEPCO. The effective way to save the energy cost is by reducing the operating energy of XCEL ENERGY plane but the most effective way is reduce the contracting energy of KEPCO plane.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.3
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• pp.460-466
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• 2018

For the efficient energy consumption in an urban railway station, it is necessary to know the patterns of electrical loads for each usage in detail. The electrical loads in an urban railway station have different characteristics from other normal electrical load, such as the peak load timing during a day. The lighting, HVAC, communication, and commercial loads make up large amount of electrical load for equipment in an urban railway station, and each of them has the unique specificity. These loads for each usage were estimated without measuring device by the polynomial regression method with big data such as total amount of electrical load and weather data. In the simulation with real data, the optimal polynomial regression model was third order polynomial regression model with 9 or 10 independent variables.