• Journal of Drive and Control
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• v.10 no.4
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• pp.43-48
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• 2013

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.225-234
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• 2015

Nowadays a Virtual Power Plant (VPP) represents an aggregation of distributed energy resource such as Distributed Generation (DG), Combined Heat and Power generation (CHP), Energy Storage Systems (ESS) and load in order to operate as a single power plant by using Information and Communication Technologies, ICT. The VPP has been developed and verified based on a single virtual plant platform which is connected with a number of various distributed energy resources. As the VPP's distributed energy resources increase, so does the number of data from distributed energy. Moreover, it is obviously inefficient in the aspects of technique and cost that a virtual plant platform operates in a centralized manner over widespread region. In this paper the concept of the large-scale VPP which can reduce a error probability of system's load and increase the robustness of data exchange among distributed energy resources will be proposed. In addition, it can directly control and supervise energy resource by making small size's virtual platform which can make a optimal resource scheduling to consider of variable and sensitive load in the large-scale VPP. It makes certain the result is verified by simulation.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.80-82
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• 2008

'08년도에 전력거래소는 에너지관리공단의 직접부하제어 설비와 고객을 인수하여 지원금입찰제에 의한 수요관리사업, 즉 수요자원시장을 구축하여 운영하였다. 곁 논문에서는 수요자원시장의 기본개념을 설명하고, 08년도 하계 수요자원시장외 운영결과와 개선방향에 대해 언급하고자 한다.

• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.1157-1160
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• 2003

We proposed a study on optimal clock period selection algorithm for low power RTL design. The proposed algorithm use the way of maintaining the throughput by reducing supply voltage after improve the system performance in order to minimize the power consumption. In this paper, it select the low power to use pipeline in the transformation of architecture. Also, the algorithm is important the clock period selection in order to maximize the resource sharing. however, it execute the optimal clock period selection algorithm.

• Environmental and Resource Economics Review
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• v.23 no.2
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• pp.349-364
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• 2014

This study analyzed Granger causality between power consumption and production activity in manufacturing sector, by using error correction model. It found that there exists the connection between power consumption and production activity in manufacturing sector. By reflecting the industrial characteristics, it found not only the bilateral causality (power consumption ${\leftrightarrow}$ production activity) in power non-intensive industry, high value-added industry and low value-added industry, but also one-way causality (power consumption ${\rightarrow}$ production activity) in power-intensive industry. These results imply that power demand management policy focusing on efficiency improvement is necessary primarily to minimize negative impacts on production activity, and also stable power supply system is required to meet the increase of power demand.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.557-581
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• 2019

This study tries to quantify the regional NIMBY costs to nuclear power plants. NIMBY costs are estimated as willingness to pays for avoiding nuclear power plants near residential areas through the contingent valuation method(CVM). In the study, it was assumed that the nuclear power plants were newly constructed around the residences. The result of 600 respondents living within a radius of 30 km of nuclear power plants compared to the result of 600 respondents living in the metropolitan area, which revealed that there were significant NIMBY costs to the construction of nuclear power plants in all residences. By region, the willingness to pay in the metropolitan area was greater than that in the nuclear power areas. This study focuses on NIMBY to nuclear power plants from a regional point of view, which can provide important information in establishing prudent and sound nuclear power policies.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.467-495
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• 2019

Uncertainty of renewable energy such as photovoltaic(PV) power is detrimental to the flexibility of the power system. Therefore, precise prediction of PV power generation is important to make the power system stable. The purpose of this study is to forecast PV power generation using meteorological data including particulate matter(PM). In this study, PV power generation is predicted by support vector machine using RBF kernel function based on machine learning. Comparing the forecasting performances by including or excluding PM variable in predictor variables, we find that the forecasting model considering PM is better. Forecasting models considering PM variable show error reduction of 1.43%, 3.60%, and 3.88% in forecasting power generation between 6am~8pm, between 12pm~2pm, and at 1pm, respectively. Especially, the accuracy of the forecasting model including PM variable is increased in daytime when PV power generation is high.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.1
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• pp.50-64
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• 2012

Quality of Service (QoS) and fairness considerations are undoubtedly essential parameters that need to be considered in the design of next generation scheduling algorithms. This work presents a novel game theoretic cross-layer design that offers optimal allocation of wireless resources to heterogeneous services in Orthogonal Frequency Division Multiple Access (OFDMA) networks. The method is based on the Axioms of the Symmetric Nash Bargaining Solution (S-NBS) concept used in cooperative game theory that provides Pareto optimality and symmetrically fair resource distribution. The proposed strategies are determined via convex optimization based on a new solution methodology and by the transformation of the subcarrier indexes by means of time-sharing. Simulation comparisons to relevant schemes in the literature show that the proposed design can be successfully employed to typify ideal resource allocation for next-generation broadband wireless systems by providing enhanced performance in terms of queuing delay, fairness provisions, QoS support, and power consumption, as well as a comparable total throughput.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.420-422
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• 2007

In order to support wind power development in Jejudo, the island of winds, the wind resource database KIER-WindJeju has been established by meteor-statistical analysis on met-mast measurements of KIER. The analysis includes tower shading, exposure category, wind profile exponent for wind speed extrapolation to hub height of wind turbine, and correlation matrix between neighboring sites to assist choice of appropriate reference site for long-term correlation. KIER-WindJeju will be provided as an add-on of Google $Earth^{TM}$ and will be used as a guideline of future wind resource assessment in Jejudo.

• 한국신재생에너지학회:학술대회논문집
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• 2006.11a
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• pp.149-152
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• 2006

New and renewable energy information becomes one of the greatest issues because of serious environment problems and limited fossil resources However, There are few system to manage and utilize new and renewable energy information efficient. Therefore this study establish the GIS based Resource Map System to save and analyze new and renewable energy Informal ion about solar energy, wind power, small hydro, biomass, and geothermal. This Resource Map System is composed of the management system, practical system, field system and Web-service system. This System can Provide var ious spatial analysis tools such as data searching, treating thematic maps, evaluating location requirements for energy facilities.