• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.1
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• pp.92-98
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• 2014

In this paper, the reconfigurable frequency selective surface for C-band was designed using patch array and grid structure. Frequency reconfigurability was obtained by varying the capacitance from varactor diode. From the optimized design parameters, we fabricated the reconfigurable frequency selective surface using the FPCB(Flexible Printed Circuit Board) and commercial varactor diode and measured the frequency reconfigurability for different bias voltage. From the measurement results, proposed structure has the wideband operating frequency of 6.6~7.6 GHz. We can applied this proposed structure to the smooth curved surface like as radome of aircraft or warship.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.9-16
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• 2012

In this paper, we propose the two dimensional variable-length vector storage format which can be used for efficient storage of sparse matrix in the FEM (finite element method). The proposed storage format is the method storing only actual needed non-zero values of each row on upper triangular matrix with the total rows N, by using two dimensional variable-length vector instead of $N{\times}N$ large sparse matrix of entire equation of finite elements. This method only needs storage spaces of the number of minimum 1 to maximum 5 in 2D grid structure and the number of minimum 1 to maximum 14 in 3D grid structure of analysis target. The number doesn't excess two times although involving index number. From the experimental result, we can find out that the proposed storage format can reduce the memory space more effectively, as the total number of nodes increases, than the existing skyline storage format storing maximum column height.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3358-3365
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• 2012

This paper presents a scheduling scheme for die casting processes considering power usage. The scheduling problem of a shift-based die casting process is represented by a linear programming (LP) model that maximizes the average efficiency of melting furnaces in regard of the usage of molten alloy, where the product quantities of each shift are used as primary variables. In this research, we propose a novel LP model that considers power usage of foundries. The developed LP model can derive product plans in which the expended power of a casting shift does not exceed a prescribed limit, while optimizing the efficiency of alloy usage. The simulation result of a case study demonstrates the superiority and applicability of the proposed scheme. This paper serves as a basic research on the role of foundries as an intelligent costumer in smart grid environment where the limit of power usage should be fulfilled.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.207-212
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• 2018

The increase in the size and the uptake of PV systems is leading to significant increase in the penetration of PV into local electricity grids. The increased penetration of PV is impacting on grid operation and in particular the voltage within the local grid can be significantly influenced by the various PV systems. The current global situation of environmental pollution, climate change and energy demand urgently requires dramatic political, economic and technical decisions in order to avoid a potential collapse of environmental and social systems. Around the world, electricity remains the vital component of national and international development. The implementation of renewable energy resources can provide solutions to these challenges by stimulating the early implementation of economically viable sustainable energy technologies.

• Journal of IKEEE
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• v.23 no.1
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• pp.127-133
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• 2019

Electric power demand forecasting is one of the important research areas for future smart grid introduction. However, It is difficult to predict because it is affected by many external factors. Traditional methods of forecasting power demand have been limited in making accurate prediction because they use raw power data. In this paper, a probability-based CRBM is proposed to solve the problem of electric power demand prediction using raw power data. The stochastic model is suitable to capture the probabilistic characteristics of electric power data. In order to compare the mid-term power demand forecasting performance of the proposed model, we compared the performance with Recurrent Neural Network(RNN). Performance comparison using electric power data provided by the University of Massachusetts showed that the proposed algorithm results in better performance in mid-term energy demand forecasting.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.2
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• pp.67-78
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• 2019

Accurate electric load forecasting is very important in the efficient operation of the smart grid. Recently, due to the development of IT technology, many works for constructing accurate forecasting models have been developed based on big data processing using artificial intelligence techniques. These forecasting models usually utilize external factors such as temperature, humidity and historical electric load as independent variables. However, due to diverse internal and external factors, historical electrical load contains many missing data, which makes it very difficult to construct an accurate forecasting model. To solve this problem, in this paper, we propose a random forest-based missing data recovery scheme and construct an electric load forecasting model based on multilayer perceptron using the estimated values of missing data and external factors. We demonstrate the performance of our proposed scheme via various experiments.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1367-1369
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• 2002

The pitch and stall schemes have some problems such as, mechanical stress, tear and wear on the transmission line, noise emission and disturbance to the grid, due to a delaying factor of mechanical process. In this paper, a novel control is developed. It serves to compensate delaying of pitch or stall schemes and allows the generate power to control in fast response. The validity of the proposed control scheme is verified by experiment results with the actual 660KW wind power system model.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.4
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• pp.305-311
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• 2013

This paper proposes a performance improvement of existing single-phase current-fed qZ-Source inverter. Voltage gain of the traditional voltage-fed full-bridge inverter and single-phase current-fed qZ-source inverter is only equal to or smaller than input voltage. The proposed inverter can obtain twice higher voltage gain than the single-phase current-fed qZ-Source inverter by adding an extra switch and a capacitor in the circuit. In addition, the proposed inverter shares the common ground between dc input and ac output voltage. Therefore, the proposed inverter can eliminate the possible ground leakage current problem when it is used for grid-tied photovoltaic inverter system. A 120 W prototype inverter is built and tested to verify performances of the proposed inverter.

• Journal of Power Electronics
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• v.12 no.1
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• pp.181-192
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• 2012

The increased penetration of Distributed Energy Resources (DER) is challenging the entire architecture of conventional electrical power system. Microgrid paradigm, featuring higher flexibility and reliability, becomes an attractive candidate for the future power grid. In this paper, an overview of microgrid configurations is given. Then, possible structure options and control methods of DER units are presented, which is followed by the descriptions of system controls and power management strategies for AC microgrids. Finally, future trends of microgrids are discussed pointing out how this concept can be a key to achieve a more intelligent and flexible power system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2027-2032
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• 2003

For action selection as well as learning, simple associations between stimulus and response have been employed in most of literatures. But, for a successful task accomplishment, it is required that an animat can learn and express behavioral sequences. In this paper, we propose a novel action-selection-mechanism to deal with sequential behaviors. For this, we define behavioral motivation as a primitive node for action selection, and then hierarchically construct a network with behavioral motivations. The vertical path of the network represents behavioral sequences. Here, such a tree for our proposed ASM can be newly generated and/or updated, whenever a new sequential behaviors is learned. To show the validity of our proposed ASM, three 2-D grid world simulations will be illustrated.