• Korean Journal of Computational Design and Engineering
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• v.15 no.1
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• pp.24-32
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• 2010

This paper introduces a B-spline based branch & bound algorithm for global optimization. The branch & bound is a well-known algorithm paradigm for global optimization, of which key components are the subdivision scheme and the bound calculation scheme. For this, we consider the B-spline hypervolume to approximate an objective function defined in a design space. This model enables us to subdivide the design space, and to compute the upper & lower bound of each subspace where the bound calculation is based on the LHS sampling points. We also describe a search tree to represent the searching process for optimal solution, and explain iteration steps and some conditions necessary to carry out the algorithm. Finally, the performance of the proposed algorithm is examined on some test problems which would cover most difficulties faced in global optimization area. It shows that the proposed algorithm is complete algorithm not using heuristics, provides an approximate global solution within prescribed tolerances, and has the good possibility for large scale NP-hard optimization.

• Journal of Power Electronics
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• v.18 no.2
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• pp.547-557
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• 2018

This work proposes a control method of frequency stabilization for grid integration of large-scale wind farms via the voltage source converter-based high-voltage direct current (VSC-HVDC) technology. First, the topology of grid integration of a large-scale wind farm via the VSC-HVDC link is provided, and simple control strategies for wind turbines, wind farm side VSC (WFVSC), and grid side VSC are presented. Second, a mathematical model between the phase angle of WFVSC and the frequency of the wind farm is established. The control principle of the large-scale wind power integrated system is analyzed in theory in accordance with the mathematical model. Third, frequency and AC voltage controllers of WFVSC are designed based on the mathematical model of the relationships between the phase angle of WFVSC and the frequency of the wind farm, and between the modulation index of WFVSC and the voltage of the wind farm. Corresponding controller structures are established by deriving a transfer function, and an optimization method for selecting the parameters of the frequency controller is presented. Finally, a case study is performed under different operating conditions by using the DIgSILENT/PowerFactory software. Results show that the proposed control method has good performance in the frequency stabilization of the large-scale wind power integrated system via the VSC-HVDC technology.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.110.4-110
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• 2002

In practical control area, there are many examples with multiple objectives which may conflict or compete with each other like overhead crane control, automatic train operation, and refuse incinerator plant control, etc. These kinds of control problems are called multiobjective control problems, where it is difficult to provide the desired performance with control strategies based on single-objective optimization. Because the conventional control theories usually treat the control problem as the single objective optimization problem , the methods are not adequate to treat the multiobjective control problems. Particularly, in case of large scale systems or ill-defined systems, the multiple obj..

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.5
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• pp.801-810
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• 2004

The Primal-Dual Interior-Point (PDIP) method is currently one of the fastest emerging topics in optimization. This method has become an effective solution algorithm for large scale nonlinear optimization problems. such as the electric Optimal Power Flow (OPF) and natural gas and electricity OPF. This study describes major theoretical developments of the PDIP method as well as practical issues related to implementation of the method. A simple quadratic problem with linear equality and inequality constraints

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.367-376
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• 2007

In this paper we consider the global convergence of a new super memory gradient method for unconstrained optimization problems. New trust region radius is proposed to make the new method converge stably and averagely, and it will be suitable to solve large scale minimization problems. Some global convergence results are obtained under some mild conditions. Numerical results show that this new method is effective and stable in practical computation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.4
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• pp.121-127
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• 1983

In this paper an efficient algorithm for Pontriagin's maximum principle is developed. Fletcher-Powell method is adopted as optimization technique which shows fast and stable convergence characteristics. Terminal constraints are alse considered by using Hestens' algorithm and penalty function method together. Control variable inequality constraints are also considered by using Gradient Projection technique combined with Flectcher-Powell method. Test experiment shows good and reliable results.

• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.332-339
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• 2003

To solve the large scale optimization problem approximately, various approaches have been introduced. Recently the Particle Swarm Optimization has been introduced. The Particle Swarm Optimization simulates the process of birds flocking or fish schooling for food, as with the information of each agent is skated by other agents. The Particle Swarm Optimization technique has been applied to various optimization problems whose variables are continuous. However, there are seldom trials for visualization of searching process. This paper proposes a new visualization tool for searching process of Particle Swarm Optimization algorithm. The proposed tool is effective for understanding the searching process of Particle Swarm Optimization method and educational for students. The computational results can be shown tiny and very helpful for education.

• Journal of Mechanical Science and Technology
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• v.16 no.8
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• pp.1033-1038
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• 2002

Genetic alsorithm (GA) , compared to the gradient-based optimization, has advantages of convergence to a global optimized solution. The genetic algorithm requires so many number of analyses that may cause high computational cost for genetic search. This paper proposes a personal computer network programming based on TCP/IP protocol and client-server model using socket, to improve processing speed of the genetic algorithm for optimization of composite laminated structures. By distributed processing for the generated population, improvement in processing speed has been obtained. Consequently, usage of network-based genetic algorithm with the faster network communication speed will be a very valuable tool for the discrete optimization of large scale and complex structures requiring high computational cost.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1348-1356
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• 2017

Integration of wind generators with the conventional power plants will raise operational challenges to the electric power utilities due to the uncertainty of wind availability. Thus, the Generation Scheduling (GS) among the online generating units has become crucial. This process can be formulated mathematically as an optimization problem. The GS problem of wind integrated power system is inherently complex because the formulation involves non-linear operational characteristics of generating units, system and operational constraints. As the robust tool is viable to address the chosen problem, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm is chosen as the main optimization tool. The intended algorithm is implemented on the standard test systems and the attained numerical results are compared with the earlier reports. The comparison clearly indicates the intended tool is robust and a promising alternative for solving GS problems.

• 한국전산유체공학회:학술대회논문집
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• 2007.10a
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• pp.100-110
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• 2007

A new design approach for a delicate treatment of complex geometries such as a wing/body configuration is arranged using overset mesh technique under large scale computing environment for turbulent viscous flow. Various pre- and post-processing techniques which are required of overset flow analysis and sensitivity analysis codes are discussed for design optimization problems based on gradient based optimization method (GBOM). The overset flow analysis code is validated by comparing with the experimental data of a wing/body configuration (DLR-F4) from the 1st Drag Prediction Workshop (DPW-I). In order to examine the applicability of the present design tools, careful design works for the drag minimization problem of a wing/body configuration are carried out by using the developed aerodynamic shape optimization tools for the viscous flow over multiple-body aircraft geometries.