• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.64-71
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• 2017

Considering the volatility, intermittent and random of photovoltaic (PV) generation systems, accurate forecasting of PV power output is important for the grid scheduling and energy management. In order to improve the accuracy of short-term power forecasting of PV systems, this paper proposes a prediction model based on environmental factors and support vector machine optimized by genetic algorithm (GA-SVM). In order to improve the prediction accuracy of this model, weather conditions are divided into three types, and the gray correlation coefficient algorithm is used to find out a similar day of the predicted day. To avoid parameters optimization into local optima, this paper uses genetic algorithm to optimize SVM parameters. Example verification shows that the prediction accuracy in three types of weather will remain at between 10% -15% and the short-term PV power forecasting model proposed is effective and promising.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.895-905
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• 2008

To analyze hydrologic processes in a watershed requires both various geographical data and hydrological time series data. Recently, not only geographical data such as DEM(Digital Elevation Model) and hydrologic thematic map but also hydrological time series from numerical weather prediction and rainfall radar have been provided as grid data, and there are studies on hydrologic analysis using these grid data. In this study, GRM(Grid based Rainfall-runoff Model) which is physically-based distributed rainfall-runoff model has been developed to simulate short term rainfall-runoff process effectively using these grid data. Kinematic wave equation is used to simulate overland flow and channel flow, and Green-Ampt model is used to simulate infiltration process. Governing equation is discretized by finite volume method. TDMA(TriDiagonal Matrix Algorithm) is applied to solve systems of linear equations, and Newton-Raphson iteration method is applied to solve non-linear term. Developed model was applied to simplified hypothetical watersheds to examine model reasonability with the results from $Vflo^{TM}$. It was applied to Wicheon watershed for verification, and the applicability to real site was examined, and simulation results showed good agreement with measured hydrographs.

• ETRI Journal
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• v.36 no.1
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• pp.80-88
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• 2014

Recently, the idea of the smart grid has been gaining significant attention and has become a hot research topic. The purpose of this paper is to present a novel smart grid management scheme that uses game theory principles. In our proposed scheme, power appliances in the smart grid adaptively form groups according to the non-cooperative hedonic game model. By exploiting multi-appliance diversity, appliances in each group are dynamically scheduled in a cooperative manner. For efficient smart grid management, the proposed coopetition game approach is dynamic and flexible to adaptively respond to current system conditions. The main feature is to maximize the overall system performance while satisfying the requirements of individual appliances. Simulation results indicate that our proposed scheme achieves higher energy efficiency and better system performance than other existing schemes.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.2
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• pp.233-244
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• 2016

Smart grid is called it as a system of systems. There are diverse types of systems in smart grid environment. Therefore, one of key factors to achieve smart grid successfully is interoperability among diverse systems. To secure interoperability, smart grid operating system should be developed complied with standards in terms of the data representation and communication. Common Information Model (CIM) and OLE Process for Control - Unified Architecture (OPC-UA) are the representative international standards in smart grid domain. Each standard defines data representation and communication by providing common information model and the unified architecture. In this paper, we explain a smart grid platform that we have developed to comply with CIM and OPC-UA standards for secure interoperability among numerous legacy systems.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.169-175
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• 2014

This paper presents an improved direct power control (DPC) strategy for grid-connected voltage source inverter (VSI) under unbalanced and harmonic grid voltage conditions. Based on the mathematic model of VSI with the negative sequence, 5th and 7th harmonic voltage components consideration, a PI controller is used in the proposed DPC strategy to achieve the average output power regulation. Furthermore, vector PI controller with the resonant frequency tuned at the two times and six times grid fundamental frequency is adopted to regulate both negative and harmonic components, and then two alternative targets of the balanced/sinusoidal current and smooth active/reactive output power can be achieved. Finally, simulation results based on MATLAB validate the availability of the proposed DPC strategy.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1822-1831
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• 2014

Micro-grid is connected to the main power grid through a static switch. One of the critical issues in micro-grids is protection which must disconnect the micro-grid from the network in short-circuit contingencies. Protective methods of micro-grid mainly follow the model of distribution system protection. This protection scheme suffers from improper operation due to the presence of single-phase loads, imbalance of three-phase loads and occurrence of power swings in micro-grid. In this paper, a new method which prevents from improper performance of static micro-grid protection is proposed. This method works based on artificial neural network (ANN) and able to differentiate short circuit from power swings by measuring impedance and the rate of impedance variations in PCC bus. This new technique provides a protective system with higher reliability.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.65-83
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• 2022

Although various statistical methods have been developed to map time-dependent genetic factors, most identified genetic variants can explain only a small portion of the estimated genetic variation in longitudinal traits. Gene-gene and gene-time/environment interactions are known to be important putative sources of the missing heritability. However, mapping epistatic gene-gene interactions is extremely difficult due to the very large parameter spaces for models containing such interactions. In this paper, we develop a Gaussian process (GP) based nonparametric Bayesian variable selection method for longitudinal data. It maps multiple genetic markers without restricting to pairwise interactions. Rather than modeling each main and interaction term explicitly, the GP model measures the importance of each marker, regardless of whether it is mostly due to a main effect or some interaction effect(s), via an unspecified function. To improve the flexibility of the GP model, we propose a novel grid-based method for the within-subject dependence structure. The proposed method can accurately approximate complex covariance structures. The dimension of the covariance matrix depends only on the number of fixed grid points although each subject may have different numbers of measurements at different time points. The deviance information criterion (DIC) and the Bayesian predictive information criterion (BPIC) are proposed for selecting an optimal number of grid points. To efficiently draw posterior samples, we combine a hybrid Monte Carlo method with a partially collapsed Gibbs (PCG) sampler. We apply the proposed GP model to a mouse dataset on age-related body weight.

• The Journal of Korean Association of Computer Education
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• v.10 no.3
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• pp.49-56
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• 2007

Grid provides a platform for the efficient execution of large-scale computing in science and engineering. In this environment, resource management and task scheduling are complex undertaking. We designed and implemented a web-based scheduling toolkit(GridTool), which can model a system and simulate scheduling scheme in Grid computing. The GridTool used GridSim, a toolkit in java-environment, as a tool for simulation. The GridTool is able to perform resource modeling, task modeling, algorithm compiling, simulation, and performance evaluation efficiently in web environment. The GridTool can be applied as a platform for Grid research and can be used to analyze the efficiency of scheduling algorithm.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.1
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• pp.64-74
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• 1997

A CELTHYM(CEll-based Long-term HYdrologic Model), a pre-processor and a post-processor that can be integrated with geographic information system(GIS) were developed to predict the stream flow from the small agricultural watershed on the daily basis. The CELTHYM calculates the direct runoff from a grid using SCS curve number method and then sum up all of cells with respect to a sub-catchment area belonged to a stream grid and integrated to an outlet. Base flow of a watershed outlet was computed by integrating of the base flow of each stream grid that was averaged the sub-catchment deep-percolation and calculated with the release rate. Two kind of water budget equation were used to compute the water balance in a grid that was classified into not paddy field and paddy field. One of the two equation is a soil water balance equation to account the soil moisture of the upland, forest and excluding paddy field grid. The other is a paddy water balance equation for the paddy field, calculating the ponding depth, the effective rainfall, the deep percolation and the evapotranspiration.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.188-197
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• 2022

We develop a coastal wave forecasting system by using the unstructured grid based on sea wind data of Global Data Assimilation and Prediction System. The verification is performed to examine the performance and accuracy of the wave model. Since the conventional grid has limited wave forecasting on complex coastlines and bathymetry, the unstructured grid system is applied for precise numerical simulation, and applicability for operational support is evaluated. Both grid systems show similar prediction trends in offshore and coastal areas, and the difference in prediction errors according to the grid system is not large. In addition, the applicability of the operational wave forecasting system is confirmed by dramatically reducing the model execution time of the unstructured grid under the same conditions.