• Transactions on Electrical and Electronic Materials
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• v.18 no.5
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• pp.287-297
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• 2017

Novel power system stabilizers (PSSs) have been proposed to effectively dampen low frequency oscillations (LFOs) in multi-machine power systems and have attracted increasing research interest in recent years. Due to this attention, recently, fractional order controllers (FOCs) have found new applications in power system stability issues. Here, a tilt-integral-derivative power system stabilizer (TID-PSS) is proposed to enhance the dynamic stability of a multi-machine power system by providing additional damping to the LFOs. The TID is an extended version of the classical proportional-integral-derivative (PID) applying fractional calculus. The design of the proposed three-parameter tunable TID-PSS is systematized as a nonlinear time domain optimization problem in which the tunable parameters are adjusted concurrently using a modified group search optimization (MGSO) algorithm. An integral of the time multiplied squared error (ITSE) performance index is considered as the objective function. The proposed stabilizer is simulated in the MATLAB/SIMULINK environment using the FOMCON toolbox and the dynamic performance is evaluated on a 3-machine 6-bus power system. The TID-PSS is compared with both classical PID-PSS (PID-PSS) and conventional PSS (CPSS) using eigenvalue analysis and time domain simulations. Sensitivity analyses are performed to assess the robustness of the proposed controller against large changes in system loading conditions and parameters. The results indicate that the proposed TID-PSS provides the better dynamic performance and robustness compared with the PID-PSS and CPSS.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1058-1062
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• 2008

In clinical decision support system(CDSS), unlike rule-based expert method, appropriate data-driven machine learning method can easily provide the information of individual feature(clinical test) for disease classification. However, currently developed methods focus on the improvement of the classification accuracy for diagnosis. With the analysis of feature importance in classification, one may infer the novel clinical test sets which highly differentiate the specific diseases or disease states. In this background, we introduce a novel CDSS that integrate a classifier and feature selection module together. Random forest algorithm is applied for the classifier and the feature importance measure. The system selects the significant clinical tests discriminating the diseases by examining the classification error during backward elimination of the features. The superior performance of random forest algorithm in clinical classification was assessed against artificial neural network and decision tree algorithm by using breast cancer, diabetes and heart disease data in UCI Machine Learning Repository. The test with the same data sets shows that the proposed system can successfully select the significant clinical test set for each disease.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.243-250
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• 2015

This paper proposes a novel skewed-type iron slot wedge that can improve both the cogging torque and the output power of a permanent magnet synchronous generator (PMSG). Generally the open slot structure is adopted in a PMSG due to its convenient winding work, but the high cogging torque is undesired. Firstly, an iron slot wedge was utilized to reduce the cogging torque of an open slot type PMSG. However, the output power of the machine decreased rapidly with this method. Thus, a proposed skewed type iron slot wedge is presented to improve the output power as well as the cogging torque as compared to the open slot type. Shape optimization of the skewed-type iron slot wedge is performed to simultaneously maximize the output power and reduce the cogging torque. The Kriging model based on the Halton sequence method and a genetic algorithm are used to optimize the design.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.43-46
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• 2003

In this paper, a novel rotor flux estimation method of an induction motor using support vector machine(SVM) is presented. Two veil-known different flux models with respect to voltage and current are necessary to estimate the rotor flux of an induction motor. The theory of the SVM algorithm is based on statistical teaming theory. Training of SVH leads to a quadratic programming(QP) problem. The proposed SVM rotor flux estimator guarantees the improvement of performance in the transient and steady state in spite of parameter variation circumstance. The validity and the usefulness of Proposed algorithm are throughly verified through numerical simulation.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.669-670
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• 2015

In this paper, rotor design modification of a novel proposed machine termed the Axial Flux Doubly Fed Reluctance Machine (AF-BDFRM) is studied. The main potential advantage of AF-BDFRM is that it has larger torque and power density compared to radial flux-BDFRM. However, with the general rotor pole shape, this machine output back EMF has high THD % and high cogging torque. This paper studies the rotor design modification in the proposed AF-BDFRM to reduce the THD % in inducedd back EMF and cogging torque. Also the transient 3D finite element analysis (FEA) optimization of initial design is presented.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.447-458
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• 2011

In this paper, a novel flywheel energy storage device, called the flexible power conditioner, which integrates both the characteristics of the flywheel energy storage and the doubly-fed induction machine, is proposed to improve power system stability. A prototype is developed and its principle, composition, and design are described in detail. The control system is investigated and the operating characteristics are analyzed. The test results based on the prototype are presented and evaluated. The test results illustrate that the prototype meets the design requirement on power regulation and starting, and provides a cost-effective and effective means to improve power system stability.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.3
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• pp.215-223
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• 2016

In this study, a novel rotor position sensorless estimation method of an interior permanent-magnet synchronous motor is proposed. A square-wave pulsating voltage signal is injected in the estimated synchronous reference frame. This signal is interpreted in the stationary reference frame regardless of the estimated rotor position. Thus, assuming that the position error is nearly zero is unnecessary because the variables in the estimated synchronous reference frame are not used. The rotor position can be exactly calculated from two voltage references and three sampled current feedbacks in the stationary reference frame. The proposed method is easy to implement and helps enhance the bandwidth of the current controller. The validity of the proposed method is verified by simulations and experiments.

• International Journal of Control, Automation, and Systems
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• v.3 no.spc2
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• pp.302-307
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• 2005

A novel neuro controller based simple neuro-structure with modified error function is introduced in this paper. This controller consists of two independent controllers, known as the voltage regulator and the angular controller. The voltage regulator is used to modify terminal voltage for the purpose of tracking a reference voltage. The angular controller is utilized to guarantee the stability of the system. In this structure each neuron uses a linear hard limit activation function that depends on the controlled variable and its derivatives. There is no need for parameter identification or any off-line training data. Two proposed controllers are merged by a smooth switch to build a complete controller. The effectiveness of the proposed novel control action is demonstrated through some computer simulations on a Single-Machine Infinite-Bus (SMIB) power system.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.3
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• pp.116-121
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• 2004

This paper proposes a novel UPFC based on 3-level Half-bridge modules, isolated through single-phase multi-winding transformers. The dynamic performance of proposed system was analyzed by simulation with EMTDC, assuming that the UPFC is connected with the 138-kV transmission line of one-machine-infinite-bus power system. The proposed system can be directly connected to the transmission line without series injection transformers. It has flexibility in expanding the operation voltage by increasing the number of 3-level Half-bridge modules.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.253-256
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• 1997

This paper describes a novel design method for compensating field time-constant of micro-synchronous machine so that its terminal flux can show the same characteristics as large-scale synchronous machine's. In addition to it, the suggested design method can determine the field time-constant regulator's parameters considered the nonlinearities of micro-synchronous machine such as saturation and loading effect. This method applied to 5kVA micro-synchronous machine, and the digital time-constant regulator with digital AVR were designed such that the short field time-constant, $T_{do}'=1.12\;sec$, can take on the large-scale synchronous machine time constant, $T_{do}'=1.47\;sec$. After determining the parameters of controllers, the real time digital time-constant regulator and digital AVR algorithm were implemented by using the PC with Penumum processor, and the usefulness of suggested real time digital time-constant regulator was verified by observing its good performance on the excitation of micro-synchronous machine.