• Advances in Energy Research
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• v.5 no.1
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• pp.79-90
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• 2017

The main objective of load frequency control (LFC) is to keep the frequency value at nominal value and force deviation of the frequency to zero in case of load change. This paper suggests LFC by using a model predictive control (MPC), based on Integral Square Error (ISE) method designed to optimize the damping of oscillations in a two-area power system. The MPC is designed and simulated with a model system in state space, for robust performance in the system response. The proposed MPC is tuned by ISE to achieve superior efficiency. Moreover, its performance has been assessed and compared with the PI and PID conventional controllers. The settling time and overshoot with MPC are extremely minimized as compared with conventional controllers.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.601-611
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• 2017

This paper proposes a simultaneous control of frequency deviation and electric vehicles (EVs) battery state of charge (SOC) using load frequency control (LFC) and EV controllers. In order to provide both frequency stabilization and SOC schedule near optimal performance within the whole operating regions, a multiple-input multiple-output model predictive control (MIMO-MPC) is employed for the coordination of LFC and EV controllers. The MIMO-MPC is an effective model-based prediction which calculates future control signals by an optimization of quadratic programming based on the plant model, past manipulate, measured disturbance, and control signals. By optimizing the input and output weights of the MIMO-MPC using particle swarm optimization (PSO), the optimal MIMO-MPC for simultaneous control of the LFC and EVs, is able to stabilize the frequency fluctuation and maintain the desired battery SOC at the certain time, effectively. Simulation study in a two-area interconnected power system with wind farms shows the effectiveness of the proposed MIMO-MPC over the proportional integral (PI) controller and the decentralized vehicle to grid control (DVC) controller.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.385-388
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• 1999

A new frequency-variant equivalent circuit model of power/ground plane is presented. The equivalent circuit is modeled with grid cells. The circuit parameters of each cell were extracted by using Fasthenry. To verify the developed circuit model, its s-parameters are compared with the measured s-parameters 〔2〕 and the full-wave simulation-based s-parameters. Consequently, it is shown that our frequency-variant equivalent circuit model can accurately predict imperfect ground effects under the high frequency operation of electronic package.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.255-261
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• 2021

This paper proposes impedance-based stability analysis of DC-DC boost converters, where a harmonic state space (HSS) modeling technique is used. At first, the HSS model of the boost converter is developed. Then, the closed-loop output impedance of the converter is derived in frequency domain using small signal modeling including frequency couplings, where harmonic transfer function (HTF) matrices of the open-loop output impedance, the duty-to-output, and the voltage controller are involved. The frequency response of the output impedance reveals a resonance frequency at low frequency region and frequency couplings at sidebands of switching frequency which agree with the simulation and experimental result.

• Earthquakes and Structures
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• v.24 no.2
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• pp.91-96
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• 2023

In this article, the vibration response of elastic nanocomposite beams with enhanced damping by nanoparticles is presented based on the mathematical model. Damp construction is considered by spring and damper elements based on the Kelvin model. Exponential shear deformation beam theory (ESDBT) has been used to model the structure. The mixed model model is used to obtain the effective properties of the structure including compaction effects. Using the energy method and Hamilton's principle, the equations of motion are calculated. The beam frequency is obtained by analytical method. The purpose of this work is to investigate the effect of volume percentage of nanoparticles and density, length and thickness of the beam on the frequency of the structure. The results show that the frequency increases with the increase in volume percentage of nanoparticles.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.1
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• pp.10-19
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• 2018

In this paper, a new high-frequency equivalent circuit model of printed spiral coils (PSCs) for radio-frequency interference (RFI) measurement has been proposed. To achieve high-frequency modeling, the proposed model consists of distributed components designed based on the design parameters of the PSCs. In addition, an analytic model for PSCs based on T-pi conversion has been proposed. To investigate the feasibility of the proposed model for RFI measurement, the transfer function between a microstrip line and a PSC has been extracted by combining the proposed model and mutual inductance. The self-impedances of the proposed model and the transfer function have been successfully validated using three-dimensional field simulation and measurements, revealing noticeable correlations up to a frequency of 6 GHz. The proposed model can be employed for high-frequency probe design and RFI noise estimation in the gigahertz range wireless communication bands.

• Journal of KSNVE
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• v.10 no.4
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• pp.648-654
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• 2000

A procedure to determine the realizable optimal positions of rigid supports is suggested to get a maximum fundamental natural frequency. a measured frequency response function based substructure-coupling technique is used to model the supported structure. The optimization procedure carries out the eigenvalue sensitivity analysis with respect to the stiffness of supports. As a result of such stiffness optimization, the optimal rigid-support positions are shown to be determined by choosing the position of the largest stiffness. The optimally determined support conditions are verified to satisfy the eigenvalue limit theorem. To demonstrate the effectiveness of the proposed method, the optimal support positions of a plate model are investigated. Experimental results indicate that the proposed method can effectively find out the optimal support conditions of the structure just based on the measured frequency response functions without any use of numerical model of the structure.

• Journal of the Korean Society of Safety
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• v.24 no.3
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• pp.96-101
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• 2009

In this study, a risk-appearance frequency evaluation model for railway level-crossing accidents is developed with the frequency estimation based on the accident history. It follows the worldwide common safety management approach and reflects the operation conditions and accident properties of the domestic railway system. The risk appearance frequency evaluation process contains a development of accident scenarios by defining the system configurations and functions, and a frequency estimation of hazardous events based on the accident history. The developed model is verified with the accident history during 5 years('03-'07) for 3 hazardous events: 'Being trapped in level crossing(Hl)', 'Crossing during warning signal(H2)' and 'Breaking through/detouring the barrier(H3)'. This risk appearance frequency evaluation model will be combined with a consequence evaluation model so as to offer full risk assessment for the railway accident. The accident risk assessment will contribute to improving the safety management of the railway system.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.111-115
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• 2024

This study builds a machine learning model optimized for clocks among various techniques in the field of artificial intelligence and applies it to clock stabilization or synchronization technology based on atomic clock noise characteristics. In addition, the possibility of providing stable source clock data is confirmed through the characteristics of machine learning predicted values during holdover of atomic clocks. The proposed machine learning model is evaluated by comparing its performance with the AutoRegressive Integrated Moving Average (ARIMA) model, an existing statistical clock prediction model. From the results of the analysis, the prediction model proposed in this study (MSE: 9.47476) has a lower MSE value than the ARIMA model (MSE: 221.2622), which means that it provides more accurate predictions. The prediction accuracy is based on understanding the complex nature of data that changes over time and how well the model reflects this. The application of a machine learning prediction model can be seen as a way to overcome the limitations of the statistical-based ARIMA model in time series prediction and achieve improved prediction performance.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.180-185
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• 2008

A new method for relative error continuous and discrete time model order reduction is proposed. The reduction technique is based on two recently developed methods, namely frequency domain balanced truncation within a frequency bound and inner-outer factorization techniques. The proposed method is of interest for practical model order reduction because in this context it shows to keep the accuracy of the approximation as high as possible without sacrificing the computational efficiency. Numerical results show the accuracy and efficiency enhancement of the method.