• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.6
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• pp.358-363
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• 2004

Due to the weather sensitivity of the power load, it is difficult to forecast accurately the peak power load of summer season. We improve the accuracy of the load forecasting considering weather condition. We introduced the sensitivity of temperature and proposed an improved forecasting algorithm. The proposed algorithm shows that the error of the load forecasting is 1.5%.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.5
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• pp.128-137
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• 1998

A numerical approach for performing kinematic design sensitivity analysis of vehicle suspension systems is presented. Compared with the conventional analytical methods, which require explicit derivation of sensitivity equations, the proposed numerical method can be applied to any type of suspension systems without obtaining sensitivity equations, once any kinematic analysis procedure is established. To obtain sensitivity equations, a numerical differentiation algorithm that uses the third order Lagrange polynomial is developed. The algorithm efficiently and accurately computes the sensitivity of various vehicle static design factors with respect to kinematic design variables. Through a suspension design problem, the validity and usefulness of the method is demonstrated.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.217-219
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• 2001

This paper presents a new eigenvalue sensitivity analysis method based on AESOPS algorithm. The additional calculation steps are derived from the original AESOPS algorithm. The additional calculation steps are performed directly from the AESOPS algorithm after iteratively calculating electro-mechanical oscillation modes in small signal stability problems. Owing to the structural characteristics of partitioned sub-matrix of state space equations, the partial differentiation terms of system state matrix for obtaining eigenvalue sensitivity indices can be calculated very simply. By the method presented in this paper, the AESOPS algorithm can be used in controller design problem as well as analysis of small signal stability problem.

• Structural Engineering and Mechanics
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• v.60 no.6
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• pp.1093-1117
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• 2016

Global sensitivity analysis (GSA) has been widely used to investigate the sensitivity of the model output with respect to its input parameters. In this paper a new single-solution search optimization algorithm is developed based on the GSA, and applied to the size optimization of truss structures. In this method the search space of the optimization is determined using the sensitivity indicator of variables. Unlike the common meta-heuristic algorithms, where all the variables are simultaneously changed in the optimization process, in this approach the sensitive variables of solution are iteratively changed more rapidly than the less sensitive ones in the search space. Comparisons of the present results with those of some previous population-based meta-heuristic algorithms demonstrate its capability, especially for decreasing the number of fitness functions evaluations, in solving the presented benchmark problems.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.835-837
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• 2002

This paper presents a shape optimization algorithm of electromagnetic devices using the design sensitivity analysis with FEM. The design sensitivity and adjoint variable formulas are derived for the 3D FEM with edge element. This algorithm is applied to 3D electro-magnet pole shape optimization problem to make a uniform flux density at the target region.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.93-99
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• 2000

In many dynamic structural optimization problems, the goal is to reduce the total weight of the structure without causing the resonance. Up to now, gradient informations(i.e., design sensitivity) have been used to achieve the goal. For some class of dynamic problems, especially coalescent eigenvalue Problems with multiobjective optimization, the design sensitivity analysis is too much complicated mathematically and numerically. Therefore, this article proposes a new technique fur structural dynamic modification using a mode modification method with Genetic Algorithm(GA). In GA formulation, fitness is defined based on penalty function approach. Design variables are iteratively improved by using genetic algorithm. Two numerical examples are shown, (ⅰ) a cantilevered plate, and (ⅱ) H-shaped structure. The results demonstrate that the proposed method is highly efficient.

• Journal of the Korea Society for Simulation
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• v.9 no.2
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• pp.89-102
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• 2000

In this paper, we consider an optimal allocation of constant service efforts in queueing network to maximize the system throughput. For this purpose, using the perturbation analysis, we apply a stochastic optimization algorithm to two types of queueing systems. Our simulation results indicate that the estimates obtained from a stochastic optimization algorithm for a two-tandem queuing network are very accurate, and those for closed loop manufacturing system are a little apart from the known optimal allocation. We find that as simulation time increases for obtaining a new gradient (performance measure with respect to decision variables) by perturbation algorithm, the estimates tend to be more stable. Thus, we consider that it would be more desirable to have more accurate sensitivity of performance measure by enlarging simulation time rather than more searching steps with less accurate sensitivity. We realize that more experiments on various types of systems are needed to identify such a relationship with regards to stopping rule, the size of moving step, and updating period for sensitivity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.11
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• pp.2007-2016
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• 2011

In this paper, a new algorithm for alleviating overloads in power networks by the use of line power tracing and sensitivity is proposed to perform line switching and bus separation effectively. Also, a new bus separation index based on line power tracing is presented to find the bus to be separated for relieving overloads effectively. By applying the sensitivity of the line flow with respect to the change of the line impedance, both switching-on and switching-off of the lines for alleviating overloads in power networks are performed systematically at once. The number of the considered cases for line switching and bus separation can be greatly reduced and the best combination of line switching and bus separation can be acquired efficiently by the use of the sensitivity and the bus separation index. In order to show the effects of this algorithm, it is applied to a small scale power system of IEEE 39-bus system and practical power systems of KEPCO.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.52 no.7
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• pp.307-314
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• 2003

This paper presents a 3D shape optimization algorithm for electromagnetic devices using the design sensitivity analysis with finite element method. The structural deformation analysis based on the deformation theory of the elastic body under stress is used for mesh renewing. The design sensitivity and adjoint variable formulae are derived for the 3D finite element method with edge element. The results of sensitivity analysis are used as the input data of the structural analysis to calculate the relocation of the nodal points. This method makes it possible that the new mesh of analysis region can be obtained from the initial mesh without regeneration. The proposed algorithm is applied to the shape optimization of 3D electromagnet pole to net a uniform flux density at the target region.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.101-108
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• 2000

An optimum design algorithm using efficient reanalysis is proposed for reliability-based optimization problems formulated as the minimization of initial cost and expected failure cost with reliability constraints. The reliability-based optimization is high cost to evaluate objective function and constraints needed reliability analysis. Therefore the sensitivity analysis of reliability index for approximated reanalysis is necessary. In this paper, three solution approaches are suggested and tested. The approaches include : (1) sensitivity analysis using finite difference; (2) sensitivity analysis using automatic differentiation (AD); and (3) sensitivity analysis with respect to intermediate variables using AD. Numerical example is optimized to show the reliability and effectiveness of the new algorithm.