• Journal of information and communication convergence engineering
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• 제5권2호
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• pp.144-149
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• 2007

Grid technologies make it possible for IT resources to be shared across organizational and security domains. The traditional identity-based access control mechanisms are unscalable and difficult to manage. Thus, we propose the FAS (Federation Agent Server) model which is composed of three modules: Certificate Conversion Module (CCM), Role Decision Module (RDM), and Authorization Decision Module (ADM). The proposed FAS model is an extended Role-Based Access Control (RBAC) model which provides resource access capabilities based on roles assigned to the users. FAS can solve the problem of assigning multiple identities to a shared local name in grid-map file and mapping the remote entity's identity to a local name manually.

• 대한토목학회논문집
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• 제28권6B호
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• pp.697-707
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• 2008

격자기반 운동파 강우유출모형 KIMSTORM(grid-based KIneMatic wave STOrm Runoff Model)은 유역의 지표흐름, 지표하흐름 및 하천흐름의 시간적 변화와 공간적 분포를 모의할 수 있다. 본 모형은 유닉스 운영체제의 C++언어로 개발되었으며, 각 셀에서의 흐름을 모의하기 위하여 단방향흐름 알고리즘과 격자기반 수문학적 물수지요소를 채택하고 있으나 운영에 몇몇 제약사항이 있다. 본 연구에서는 기존모형을 개선하고자 하였으며, MS Windows 운영체제에서 실행 가능하도록 FORTRAN 90 언어를 이용하여 ModKIMSTORM을 개발하였다. 기존모형에 비해 개선된 주요사항으로, 물리적 기반의 침투기법인 GAML(Green-Ampt & Mein-Larson) 침투모형 추가, 격자 유출심과 Manning 조도계수에 의한 논에서의 지표유출 제어, 지표격자의 기저유출 요소 추가, 공간강우와 지점강우의 처리, 전 후 처리부문 개발, 5개 평가항목(피어슨의 결정계수 $R^2$, Nash & Sutcliffe 모형효율 E, 유출용적 편차 $D_v$, 첨두유출의 상대오차 $EQ_p$, 첨두시간의 절대오차 $ET_p$)을 이용한 모의결과의 자동 평가 기능을 개발하였다. 추가적으로, 모형의 계산효율을 향상시키고 지표격자의 기저유출을 하천격자로 이송하기 위하여 쉘정렬 알고리즘을 채택하였다. 모형의 입력자료는 ESRI ArcInfo W/S 또는 ArcView와 같은 GIS 소프트웨어 및 MS Excel을 이용하여 간단히 구축할 수 있으며, 모의결과의 공간적 분포를 확인할 수 있는 토양수분, 지표유출, 유출심 및 유속분포도는 BSQ, ESRI ASCII Grid, ESRI Binary Grid 및 IDRISI Raster 형식으로 출력할 수 있도록 개선하였다.

• Journal of Electrical Engineering and Technology
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• 제7권5호
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• pp.698-704
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• 2012

This paper proposes a new methodology for evaluating the probabilistic reliability based grid expansion planning of composite power system including the Wind Turbine Generators. The proposed model includes capacity limitations and uncertainties of the generators and transmission lines. It proposes to handle the uncertainties of system elements (generators, lines, transformers and wind resources of WTG, etc.) by a Composite power system Equivalent Load Duration Curve (CMELDC)-based model considering wind turbine generators (WTG). The model is derived from a nodal equivalent load duration curve based on an effective nodal load model including WTGs. Several scenarios are used to choose the optimal solution among various scenarios featuring new candidate lines. The characteristics and effectiveness of this simulation model are illustrated by case study using Jeju power system in South Korea.

• 정보처리학회논문지A
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• 제13A권1호
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• pp.35-44
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• 2006

그리드 자원의 안정적인 수요와 공급이 뒷받침되기 위해서는 유틸리티 모델을 지향하는 그리드 어카운팅 모델이 필수적이다. 현재 개발된 대부분의 그리드 어카운팅 시스템들은 로컬 어카운팅 시스템을 변경함으로써 사이트의 자율성을 침해하거나, 사이트의 가격 정책에 따른 가변 비용을 고려하지 않은 채로 그리드 서비스에 대한 과금을 산출하고 있다. 본 논문에서는 그리드 컴퓨팅 환경에 참여하는 사이트의 자율성을 보장하면서, 다양한 과금 정책에 능동적으로 대처할 수 있는 사이트 가격 정책 기반의 그리드 어카운팅 모델을 제안한다. 또한 그리드에 참여하는 엔티티들간에 어카운팅 정보를 상호 교환할 수 있도록 GGF-UR 포맷으로 변환하여 Resource Usage Service가 가능하도록 제안한다. 그리고 본 논문에서 제안하는 그리드 어카운팅 모델은 기존의 어카운팅 시스템들에 비해 사이트의 자율성을 보장하면서 정교한 과금 정책을 필 수 있는 비즈니스 모델로 평가된다.

• 전기학회논문지
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• 제56권5호
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• pp.841-847
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• 2007

This paper deals with the micro-grid consisting of micro-sources which adopt voltage sourced inverters with independent real and reactive power control capability for providing premium power quality. This paper presents dynamic modeling and the stable operating range of the micro-grid system varying the parameters of the micro-sources. The fundamental frequency model of the micro-source inverters are considered to form a dynamic model of the micro-grid system. Stability analysis is performed based on the linearized dynamic model of the micro-grid system. Case study results show the parameters affecting the stability of the micro-grid and the stable operating range of the micro-sources.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.989-995
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• 2017

As is known to all that the output of wind power generation has a character of randomness and volatility because of the influence of natural environment conditions. At present, the research of wind power prediction mainly focuses on point forecasting, which can hardly describe its uncertainty, leading to the fact that its application in practice is low. In this paper, a wind power range prediction model based on the multiple output property of BP neural network is built, and the optimization criterion considering the information of predicted intervals is proposed. Then, improved Particle Swarm Optimization (PSO) algorithm is used to optimize the model. The simulation results of a practical example show that the proposed wind power range prediction model can effectively forecast the output power interval, and provide power grid dispatcher with decision.

• 한국물환경학회지
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• 제28권1호
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• pp.26-37
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• 2012

Multi-dimensional hydrodynamic and water quality models are widely used to simulate the physical and biogeochemical processes in the surface water systems such as reservoirs and estuaries. Most of the models have adopted the Eulerian grid modeling framework, mainly because it can reasonably simulate physical dynamics and chemical species concentrations throughout the entire model domain. Determining the optimum grid cell size is important when using the Eulerian grid-based three-dimensional water quality models because the characteristics of species are assumed uniform in each of the grid cells and chemical species are represented by concentration (mass per volume). The objective of this study was to examine the effect of grid-size of a three dimensional hydrodynamic and water quality model (EFDC) on hydrodynamics and mass transport in the Saemangeum Reservoir. Three grid resolutions, respectively representing coarse (CG), medium (MG), and fine (FG) grid cell sizes, were used for a sensitivity analysis. The simulation results of numerical tracer showed that the grid resolution affects on the flow path, mass transport, and mixing zone of upstream inflow, and results in a bias of temporal and spatial distribution of the tracer. With the CG, in particular, the model overestimates diffusion in the mixing zone, and fails to identify the gradient of concentrations between the inflow and the ambient water.

• Journal of Communications and Networks
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• 제18권3호
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• pp.484-492
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• 2016

Smart grid (SG) technology is now elevating the conventional power grid system to one that functions more cooperatively, responsively, and economically. When applied in an SG the demand side management (DSM) technique can improve its reliability by dynamically changing electricity consumption or rescheduling it. In this paper, we propose a new SG scheduling scheme that uses the DSM technique. To achieve effective SG management, we adopt a mixed pricing strategy based on the Rubinstein-Stahl bargaining game and a repeated game model. The proposed game-based pricing strategy provides energy routing for effective energy sharing and allows consumers to make informed decisions regarding their power consumption. Our approach can encourage consumers to schedule their power consumption profiles independently while minimizing their payment and the peak-to-average ratio (PAR). Through a simulation study, it is demonstrated that the proposed scheme can obtain a better performance than other existing schemes in terms of power consumption, price, average payment, etc.

• 한국멀티미디어학회논문지
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• 제22권8호
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• pp.913-922
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• 2019

The Internet of Things (IoT) envisions smart objects collecting and sharing data at a massive scale via the Internet. One challenging issue is how to disseminate data to relevant data consuming objects efficiently. In such a massive IoT network, Mission critical data dissemination imposes constraints on the message transfer delay between objects. Due to the low power and communication range of IoT objects, data is relayed over multi-hops before arriving at the destination. In this paper, we propose a quorum-based adaptive dissemination algorithm (QADA) for the critical data in the monitoring-based applications of massive IoTs. To design QADA, we first design a new stepped-triangular grid structures (sT-grid) that support data dissemination, then construct a triangular grid overlay in the fog layer on the lower IoT layer and propose the data dissemination algorithm of the publish/subscribe model that adaptively uses triangle grid (T-grid) and sT-grid quorums depending on the mission critical in the overlay constructed to disseminate the critical data, and evaluate its performance as an analytical model.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• 제10권S_1호
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• pp.23-28
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• 2001

A new numerical weather prediction and dispersion model, the Operational Multi-scale Environment model with Grid Adaptivity(OMEGA) including an embedded Atmospheric Dispersion Model(ADM), is introduced as a next generation atmospheric simulation system for real-time hazard predictions, such as severe weather or the transport of hazardous release. OMEGA is based on an unstructured grid that can facilitate a continuously varying horizontal grid resolution ranging from 100 km down to 1 km and a vertical resolution from 20 -30 meters in the boundary layer to 1 km in the free atmosphere. OMEGA is also naturally scale spanning and time. In particular, the unstructured grid cells in the horizontal dimension can increase the local resolution to better capture the topography or important physical features of the atmospheric circulation and cloud dynamics. This means the OMEGA can readily adapt its grid to a stationary surface, terrain features, or dynamic features in an evolving weather pattern. While adaptive numerical techniques have yet to be extensively applied in atmospheric models, the OMEGA model is the first to exploit the adaptive nature of an unstructured gridding technique for atmospheric simulation and real-time hazard prediction. The purpose of this paper is to provide a detailed description of the OMEGA model, the OMEGA system, and a detailed comparison of OMEGA forecast results with observed data.