• Advances in Energy Research
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• 제5권1호
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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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• 제12권2호
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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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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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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• 제7권2호
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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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• 제24권2호
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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.

• 한국전자파학회논문지
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• 제29권1호
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• pp.10-19
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• 2018

본 논문에서는 고주파 Radio-Frequency Interference (RFI) 측정용 프로브로 널리 쓰이는 Printed Spiral Coil(PSC)의 고주파 등가회로 모델이 제안되었다. 제안된 모델은 고주파 정합성을 확보하기 위하여 PSC의 설계변수에 기반한 분포 모델로 설계되었으며, 제안된 분포 등가회로 모델을 바탕으로 T-Pi 등가변환을 이용한 PSC의 고주파 해석적 모델 역시 새로이 제안되었다. 제안된 모델의 실제 고주파 RFI 측정 시 효용성을 확인하기 위하여, 임의의 RFI 노이즈 원으로 설계된 마이크로스트립 라인과 PSC 사이의 전달함수를 제안된 모델과 상호 인덕턴스를 결합하여 추출하였다. 제안된 PSC 모델의 자기 임피던스(self-impedance)와 전달함수는 3-dimensional field solver를 이용한 시뮬레이션 및 실 측정으로 검증되었으며, 6 GHz까지 높은 정합성을 보이는 것이 확인되었다. 제안된 PSC의 자기 임피던스 및 전달함수 모델은 GHz 영역의 고주파 통신대역에서의 RFI 측정용 프로브 설계 및 노이즈 간섭 예측에 활용될 수 있다.

• 소음진동
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• 제10권4호
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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.

• 한국안전학회지
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• 제24권3호
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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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• 제13권1호
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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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• 제6권2호
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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.