• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1329-1339
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• 2017

This paper presents the power scheduling of a multi-microgrid (MMG) system using an optimization technique called particle swarm optimization (PSO). The PSO technique has been shown to be most effective at solving the various problems of the economic dispatch (ED) in a power system. In addition, a new MMG system configuration is proposed in this paper, through which the optimal power flow is achieved. Both optimization and power trading methods within an MMG are studied. The results of implementing PSO in an MMG system for optimal power flow and cost minimization are obtained and compared with another attractive and efficient optimization technique called the genetic algorithm (GA). The comparison between these two effective methods provides very competitive results, and their operating costs also appear to be comparable. Finally, in this study, power scheduling and a power trading method are obtained using the MATLAB program.

• Bulletin of the Korean Mathematical Society
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• v.51 no.3
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• pp.717-737
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• 2014

We study the effect of numerical quadrature in space on semidiscrete and fully discrete piecewise linear finite element methods for parabolic interface problems. Optimal $L^2(L^2)$ and $L^2(H^1)$ error estimates are shown to hold for semidiscrete problem under suitable regularity of the true solution in whole domain. Further, fully discrete scheme based on backward Euler method has also analyzed and optimal $L^2(L^2)$ norm error estimate is established. The error estimates are obtained for fitted finite element discretization based on straight interface triangles.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.485-487
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• 1999

We propose the algorithm with which one can solve the problem of the two-level hierarchical optimal control of nonlinear systems by repeatedly updating the state vectors using the haar function and Picard's iteration methods. Using the simple operation of the coefficient vectors from the fast haar transformation in the upper level and applying that vectors to Picard iteration methods in the independently lower level allow us to obtain the another method except the inversion matrix operation of the high dimention and the kronecker product in the optimal control algorithm.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.350-353
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• 2000

This paper presents an algorithm for Optimal Reactive Power Dispatch(ORPD) problem based on genetic algorithm. Optimal reactive power dispatch is particularized to the minimization of transmission line losses by suitable selection of generator reactive power outputs and transformer tap settings. To reduce system loss and improve voltage profile, two methods, Loss Re-Distribution Algorithm (LRDA) and Voltage Dependent Load Model (VDLM), are applied to ORPD. The proposed methods have been evaluated on the IEEE 30 bus system. Each of results have been compared with result of load flow.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.135-141
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• 2009

A variety of statistical methods are applied to model and optimize responses, related to product or system's quality, in terms of control and noise factors at design and manufacturing stages. Most of them assume continuous response variables but, assessing the performance of a product or system often involves categorical observations, such as ratings and scores. Although most previous works to deal with the categorical data provide sorhisticated response models and ensure unbiased outcomes, they require heavy computation to estimate the model parameters, as well as enough replications. In this study, we present some practical approaches for optimal parameter design with ordered categorical response when only a few or no replication is available. Two real-life examples are given to illustrate the presented methods.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1265-1268
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• 1996

This paper describes a new pulse width modulation (PWM) scheme suitable for microprocessor-based PWM inverters. Optimal switching patterns minimizing the performance index corresponding to the distortion factor are decided in real time by numerical calculation using the microprocessor-implemented control system. This PWM method is compared with conventional methods, such as the natural PWM and the direct PWM. Harmonic analysis using digital simulations shows that the proposed PWM scheme has much less low-order harmonics than the other methods. The validity of this method is verified in experiments using a microprocessor-based control system, where a 16-bit single-chip microcontroller, Intel 80c196kc is used.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.4-5
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• 2014

Planning earthmoving haul-route must be preceded for appropriate equipment fleet assignment. However, traditional haul-route planning methods have limitations relative to practical usage because multiple variables (e.g., grade/rolling resistance, length, equipment's weight etc.) should be considered at a time. Genetic algorithm(GA) was introduced to improve these traditional methods. However, GA based haul-route planning method still remains in inefficiency relative to computation performance. This study presents a new haul-route searching method that computes an optimal haul-route using GA. The system prototype is developed by using MATLAB(ver. 2008b). The system identifies an optimal haul-route by considering equipment type, soil type, and soil condition.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.38.5-38
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• 2001

In this paper, we propose new digital optimal control approach for controlling continuous-time nonlinear chaotic systems, which show very complex behavior and cannot be easily controlled by conventional control methods. Most real systems are represented as continuous-time system, whereas some control methods should be implemented under the condition of computer-based platforms, which are discrete-time systems. To achieve the control objective for chaotic systems successfully, the sampled-data controller, which considers the inter-sample behavior of the continuous-time systems effectively, should be needed. The proposed optimal controller is designed based on the linearized estimation model of chaotic systems. By the computer simulation, we show the control ...

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.451-459
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• 2008

Accurate load modeling is essential for power system static and dynamic analysis. By the nature of the problem of parameter estimation for power system load modeling using actual measurements, multiple local optimal solutions may exist and local methods can be trapped in a local optimal solution giving possibly poor performance. In this paper, Trust-Tech, a novel methodology for global optimization, is applied to tackle the multiple local optimal solutions issue in measurement-based power system load modeling. Multiple sets of parameter values of a composite load model are obtained using Trust-Tech in a deterministic manner. Numerical studies indicate that Trust-Tech along with conventional local methods can be successfully applied to power system load model parameter estimation in measurement-based approaches.

• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.61-82
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• 2000

In this paper two so-called regularized Green's functions are introduced to derive the optimal maximum norm error estimates for the unknown function and the adjoint vector-valued function for mixed finite element methods of Laplacian operator. One contribution of the paper is a demonstration of how the boundedness of $L^1$-norm estimate for the second Green's function ${\lambda}_2$ and the optimal maximum norm error estimate for the adjoint vector-valued function are proved. These results are seemed to be to be new in the literature of the mixed finite element methods.