• Journal of information and communication convergence engineering
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• v.5 no.2
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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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.697-707
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• 2008

The grid-based KIneMatic wave STOrm Runoff Model (KIMSTORM) by Kim (1998) predicts the temporal variation and spatial distribution of overland flow, subsurface flow and stream flow in a watershed. The model programmed with C++ language on Unix operating system adopts single flowpath algorithm for water balance simulation of flow at each grid element. In this study, we attempted to improve the model by converting the code into FORTRAN 90 on MS Windows operating system and named as ModKIMSTORM. The improved functions are the addition of GAML (Green-Ampt & Mein-Larson) infiltration model, control of paddy runoff rate by flow depth and Manning's roughness coefficient, addition of baseflow layer, treatment of both spatial and point rainfall data, development of the pre- and post-processor, and development of automatic model evaluation function using five evaluation criteria (Pearson's coefficient of determination, Nash and Sutcliffe model efficiency, the deviation of runoff volume, relative error of the peak runoff rate, and absolute error of the time to peak runoff). The modified model adopts Shell Sort algorithm to enhance the computational performance. Input data formats are accepted as raster and MS Excel, and model outputs viz. soil moisture, discharge, flow depth and velocity are generated as BSQ, ASCII grid, binary grid and raster formats.

• Journal of Electrical Engineering and Technology
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• v.7 no.5
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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.

• The KIPS Transactions:PartA
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• v.13A no.1 s.98
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• pp.35-44
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• 2006

Grid accounting model is necessary to support the demand and supply of id resource. Most grid accounting systems currently in use intrude upon site autonomy by modifying local accounting systems or calculate the cost of grid service without regard to site price policy. In this paper we propose and design Grid accounting model based on site price policy. This model assures autonomy of sites participating in gird computing and be able to actively cope with diverse billing services. Also this proposed model enables to provide RUS to Grid entities by transforming basic accounting information into GGF-UR format and allows this entities to exchange resource usage information. In this paper, proposed Grid accounting model enables sites to have autonomy of them and is evaluated for business model to enforce elaborate charging policy, compared with other systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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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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• v.12 no.3
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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.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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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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• v.18 no.3
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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.

• Journal of Korea Multimedia Society
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• v.22 no.8
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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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• v.10 no.S_1
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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.