• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.638-644
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• 2010

This paper presents ideas of service scenarios for home residents using electric power monitoring system per appliance, the implementation of the monitoring system, and analysis of acquired electric power usage pattern. By acquiring and analyzing electric power usage pattern, home residents can get information of power usage pattern of every legacy (non-Demand Response-ready) appliance. Further they can get pieces of recommendation how to reduce energy consumption, intelligent standby power blocking service, and alarming service to abnormality of appliances. In order to check the feasibility of the ideas, a system that can acquire electric power pattern per appliance is implemented, and electric power pattern of some appliances are stored to a database and it was analyzed to show if auto-identification of a type of a device is possible, which is a basic required function for the scenarios presented.

• Spatial Information Research
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• v.19 no.1
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• pp.61-72
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• 2011

Greenhouses gas emission due to usage of fossil fuel has been known as one of the main causes of global warming. Fundamentally, greenhouse gas is a by-product of economic activity. Since majority of economic activity happens in an urban setting, a countermeasure in an urban setting is needed. Therefore, an analysis of relationship between carbon dioxide emission and urban form will be investigated for urban planning and management in the future. The purpose of this study is to analyze the relationship between carbon dioxide emission and urban spatial patterns, and suggesting an urban form with low carbon dioxide emission. In order to achieve this, first theoretical analysis was carried out on urban spatial patterns related to physical size, usage rate, and activity level. Secondly, Seoul's dam on electricity, natural gas, local heating, petroleum, and water usage and mapping a carbon dioxide emission map. Thirdly, relationship between carbon dioxide emission and urban spatial patterns are analyzed and urban spatial patterns that affects energy usage in urban setting was elucidated, and elicited implications on future directions on urban planning based on our analyses above.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.5
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• pp.559-565
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• 2010

In this study we propose noise energy harvesting for green infrastructure development. In this regard, infrastructures such as railroad, subway, and road are taken into consideration as sources of noise which provides energy through certain wave forms. As the need of recycling noise energy became reasonable due to the increase of infrastructure usage, the capacity and property of our noise energy generating device, which uses electromagnetic induction for electricity generation, are analysed in this paper. Consequently, the outcomes of this experiment show the fact that maximum electricity is generated from the device at a specific point of noise frequency, and the relation between air pressure caused by noise and the electricity generated by the device is in a specific proportional form either linear or non-linear. The major points of developing noise energy generating device in order to apply it into social infrastructure are discussed in this paper as well.

• KIEAE Journal
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• v.13 no.6
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• pp.55-65
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• 2013

Korean Government has developed Sejong City as a new administration city. This city of future was planned and designed toward one of the most eco-friendly city on the basis of ICTs. To attain this object, a carbon emission monitoring system (CEMS) was designed and installed as a part of u-city service which provides various information anytime and anywhere to enrich the people's quality of life. In this paper, at first, the structure and functions of CEMS are introduced. This system is consist of 5 parts - data collection from user and linked public DBs, transforming data into meaningful information for the policy makers, system-user interfacing via statistical tables and graphs, and system maintenance. This system can be operated by the citizen participation through whole the process. With the help of GIS map and graphic interface, statistics of monitored data for both citizen and decision maker provided and after feed-back, they have affected on the behaviour of citizen's energy consumption and related policy as well. By the CEMS, energy consumption data of 124 agreed households were collected during 9 months in 2012. Electricity, gas and water consumption were remote-metered automatically by the system and analysed. This showed that more than 85% of CO2 emission is rely on electricity usage. Furthermore, number of family members and size of house influences on the emission of CO2 by each household together with the life-style of the occupants. Electricity and water consumption showed the seasonal factor while gas consumption represents the number of family members. Even this paper has limitations caused by 9 months of data collection, it shows the policy directions to reduce the emission of CO2 focusing on the house size and number of family members of each households. With the result of this research, life-style of the generation of dwellers should be investigated and the CO2 emission characteristics of other housing type as well for the data building for future policy making.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.30 no.3
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• pp.130-142
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• 2018

We use heat pumps with thermal storage system to reduce peak usage of electric power during winters and summers. A heat pump stores thermal energy in a thermal storage tank during the night, to meet load requirements during the day. This system stabilizes the supply and demand of electric power; moreover by utilizing the inexpensive midnight electric power, thus making it cost effective. In this study, we propose a system wherein the thermal storage tank and heat pump are modeled using the TRNSYS, whereas the control simulations are performed by (i) conventional control methods (i.e., thermal storage priority method and heat pump priority method); (ii) region control method, which operates at the optimal part load ratio of the heat pump; (iii) load response control method, which minimizes operating cost responding to load; and (iv) dynamic programming method, which runs the system by following the minimum cost path. We observed that the electricity cost using the region control method, load response control approach, and dynamic programing method was lower compared to using conventional control techniques. According to the annual simulation results, the electricity cost utilizing the load response control method is 43% and 4.4% lower than those obtained by the conventional techniques. We can note that the result related to the power cost was similar to that obtained by the dynamic programming method based on the load prediction. We can, therefore, conclude that the load response control method turned out to be more advantageous when compared to the conventional techniques regarding power consumption and electricity costs.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.791-804
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• 2020

Residential electricity consumption can be predicted more accurately by utilizing the realtime household electricity consumption reference that can be collected by the AMI as the ICT developed under the smart grid circumstance. This paper studied the model that predicts residential power load using the ARIMA, TBATS, NNAR model based on the data of hour unit amount of household electricity consumption, and unlike forecasting the consumption of the whole households at once, it computed the anticipated amount of the electricity consumption by aggregating the predictive value of each established model of cluster that was collected by the households which show the similiar load profile. Especially, as the typical time series data, the electricity consumption data chose the clustering analysis method that is appropriate to the time series data. Therefore, Dynamic Time Warping and Periodogram based method is used in this paper. By the result, forecasting the residential elecrtricity consumption by clustering the similiar household showed better performance than forecasting at once and in summertime, NNAR model performed best, and in wintertime, it was TBATS model. Lastly, clustering method showed most improvements in forecasting capability when the DTW method that was manifested the difference between the patterns of each cluster was used.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.4
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• pp.65-74
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• 2010

This study is for Hanbuk Mountain Range within Gyeonggi province which is to propose the conservation plan by each damage pattern through site survey of the mountain range. The damage patterns are classified by siding, pointing and lining. The total damaged area is 103 areas: The siding pattern is damaged by developing farmland, mineral and quarry mining, dam, large scale development complex and cemetery park; The pointing pattern is including the development of road, transmission tower and way and mountaineering trail; The construction of electricity and communication facility, military facility, mobile communication station, heliport and shelter. The damages by developing road and large scale development complex are the most cause, and military facility, dam and reservoir, and residential area are the main causes, respectively. One of the compromised situation Hanbuk-Mountain Range usage as per section 7 section (18.45%), 12 section (18.45%) is the largest number of compromised has been surveyed, undermine the situation if you look at the usage by the road 25 locations (24.22%), military facilities and dam and reservoir to undermine this 11 established respectively (10.68%) were the most undermine. Therefore, this research propose the conservation plan as follow: first, need to understand, educate and publicize on Hanbuk-Mounatin Range; second, manage through the regulations and ordinance of Gyeonggi province; third build and expand the law for protecting Baekdu-Great Mountain Range.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.766-769
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• 2005

In a ubiquitous environment made up of multiple sensors, most sensors participate in communications with limited battery, and the sensor node isn't able to participate in communications when all the battery is used up. When an existing authentication method is used for the sensor node which has to participate in a long term communication with limited battery, it creates a problem by making the length of network maintenance or sensor node's operation time relatively shorte. Therefore, a network structure where RM (Register Manager) node and AM (Authentication Manager) node are imported to solve the energy consumption problem during a communication process is presented in this thesis. This offers a low power protocol based on safety through a mutual authentication during communications. Through registration and authentication manager nodes, each sensor nodes are ensured of safety and the algorithm of key's generation, encryption/descramble and authentication is processed with faster operation speed. So the amount of electricity used up during the communications between sensor nodes has been evaluated. In case of the amount of electrical usage, an average of $34.783\%$ for the same subnet and 36.855 for communications with two different subnets, are reduced. The proposed method is a protocol which maintains the limited battery for a long time to increase the effectiveness of energy usage in sensor nodes and can also increase the participation rate of communication by sensor nodes.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.372-374
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• 2008

Korea classified into a development country when UNFCCC was concluded in 1995. So Korea doesn't have a GHG reduction duty until 2012. As the UNFCCC is strengthened, recently there is a growing interest in renewable energy and energy usage efficiency improvement for reducing GHG emission. It is associated with CES and renewable energy. CES is a total energy (heat, cooling and power)supplier in aggregated demand zone like a hotel, building, hospital and redevelopment district using CHP and it improves energy usage efficiency. At present, renewable energy is needed for GHG reduction duty but renewable energy doesn't have economic feasibility. So renewable energy is needed various support system to popularize which is a FIT and RPS. Especially RPS is carrying out instead of FIT in many advanced country and it will be inroduced in Korea. RPS is a duty which electricity service provider must guarantee renewable energy as much as specific ratio of total capacity. Therefore this study conducts an economic feasibility estimation of CES considering renewable energy when RPS will introduced in the future.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.68-77
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• 2018

Regarding demand response (DR) by residential users (R-users), the users try to reduce electricity costs by adjusting their power consumption in response to the time-varying price. However, their power consumption may be affected not only by the price, but also by user convenience for using appliances. This paper proposes a methodology for appliance scheduling (AS) that considers the user convenience based on historical data. The usage pattern for appliances is first modeled applying the copula function or clustering method to evaluate user convenience. As the modeling results, the comfort distribution or representative scenarios are obtained, and then used to formulate a discomfort index (DI) to assess the degree of the user convenience. An AS optimization problem is formulated in terms of cost and DI. In the case study, various AS tasks are performed depending on the weights for cost and DI. The results show that user convenience has significant impacts on AS. The proposed methodology can contribute to induce more DR participation from R-users by reflecting properly user convenience to AS problem.