• The Transactions of the Korean Institute of Electrical Engineers
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• v.33 no.10
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• pp.410-422
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• 1984

This paper presents a new practical method for optimal active and reactive power control for the economic operation in electrical power system, and the programs are developed for digital computer solution. The major features and techniques of this paper are as follows: 1) The method is presented for finding the equivalent active power balance equation applying the sparse Jacobian matrix of power flow equation instead of using B constant as active power balance equation considering transmission loss, and thus for determining directly optimal active power allocation berween generator unitw satisfying the equality and inequality constraints. 2) The method is proposed for solving directly the optimum economim dispatch problem without using gradient method and penalty function for both active and reactive power control. As a result, the computing time are reduced and convergence characteristic is remarkably improved. 3) Unlike most of conventional methods which adopt the transmission loss as a objective function for reactive power control, the total fuel cost of themal power plant is adopted as objective function for both active and reactive power control. consequently, more reasonable and economic profit can be achieved.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.16-18
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• 2004

The flexible AC transmissions system (FACTS) is the underpinning concept upon which are based promising means to avoid effectively power flow bottlenecks and ways to extend the loadability of existing power transmission networks. This paper proposes a method by which the optimal locations of the FACTS to be installed in power system under cost function. The optimal solution of this type of problem requires large scale nonlinear optimization techniques. We used Lagrange multipliers to solve a nonlinear equation with equality and ineaquality constraints. Case studies on the standard IEEE 14 bus system show that the method can be implemented successfully and that it is effective for determining the optimal location of the FACTS.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.16-24
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• 2022

This paper presents a method that can reduce the computational cost of the hierarchical quadratic programming (HQP)-based robot controller. Hierarchical controllers can effectively manage articulated robots with many degrees of freedom (DoFs) to perform multiple tasks. The HQP-based controller is one of the generic hierarchical controllers that can provide a control solution guaranteeing strict task priority while handling numerous equality and inequality constraints. However, according to a large amount of computation, it can be a burden to use it for real-time control. Therefore, for practical use of the HQP, we propose a method to reduce the computational cost by decreasing the size of the decision variable. The computation time and control performance of the proposed method are evaluated by real robot experiments with a 15 DoFs dual-arm manipulator.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_1
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• pp.659-667
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• 2021

This paper develops the theory for a novel fault-tolerant, permanent magnet biased, 4-active-pole, double plane, homopolar magnetic bearing. The Lagrange Multiplier optimization with equality constraints is utilized to calculate the optimal distribution matrices for the failed bearing. If any of the 4 coils fail, the remaining three coil currents change via a novel distribution matrix such that the same opposing pole, C-core type, control fluxes as those of the un-failed bearing are produced. Magnetic flux coupling in the magnetic bearing core and the optimal current distribution helps to produce the same c-core fluxes as those of unfailed bearing even if one coil suddenly fails. Thus the magnetic forces and the load capacity of the bearing remain invariant throughout the failure event. It is shown that the control fluxes to each active pole planes are successfully isolated. A numerical example is provided to illustrate the new theory.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_1
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• pp.231-238
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• 2023

This paper develops the theory for a novel fault-tolerant, permanent magnet biased, 6-active-pole, homopolar magnetic bearing. The Lagrange Multiplier optimization with equality constraints is utilized to calculate the optimal distribution matrices for the failed bearing. some numerical examples of distribution matrices are provided to illustrate the new theory. Simulations show that very much the same dynamic responses (orbits or displacements) are maintained throughout failure events (up to any combination of 3 coils failed for the 6 pole magnetic bearing) while currents and fluxes change significantly. The overall load capacity of the bearing actuator is reduced as coils fail. The same magnetic forces are then preserved up to the load capacity of the failed bearing.

• Elastomers and Composites
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• v.34 no.4
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• pp.321-331
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• 1999

The curing process is the final step in tire manufacturing whereby a green tire built from layers of rubber compounds is formed to the desired shape and the compounds are converted to a strong, elastic materials to meet tire performance needs under elevated pressure and temperature in a press. A numerical optimization procedure was developed to improve product quality in a tire curing process. First, a dynamic constrained optimization problem was formulated to determine the optimal condition of the supplied cure media during a curing process. The objective function is subject to an equality constraint representing the process model that describes the heat transfer and cures kinetic phenomena in a cure press and is subject to inequality constraints representing temperature limits imposed on cure media. Then, the optimization problem was solved to determine optimal condition of the supplied cure media for a tire using the complex algorithm along with a finite element model solver.

• Computational Structural Engineering
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• v.9 no.3
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• pp.169-177
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• 1996

The focus of this study is on the problem of the design of structure of undetermined topology. This problem has been regarded as being the most challenging of structural optimization problems, because of the difficulty of allowing topology to change. Conventional approaches break down when element sizes approach to zero, due to stiffness matrix singularity. In this study, a novel nonlinear programming formulation of the topology problem is presented. Its main feature is the ability to account for topology variation through zero element sizes. Stiffness matrix singularity is avoided by embedding the equilibrium equations as equality constraints in the optimization problem. Although the formulation is general, two dimensional plane elasticity examples are presented. The design problem is to find minimum weight of a plane structure of fixed geometry but variable topology, subject to constraints on stress and displacement. Variables are thicknesses of finite elements, and are permitted to assume zero sizes. The examples demonstrate that the formulation is effective for finding at least a locally minimal weight.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.2
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• pp.153-161
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• 2009

A domain/boundary decomposition method is applied for efficient analyses of thermo-elasto-viscoplastic damage and contact problems under the assumption of infinitesimal deformation. For the decomposition of a whole domain and contact boundaries, all the equality constraints on the interface and contact interfaces are restated with simple penalty functional. Therefore, the non-linearity of the problem is localized within finite element matrices in a few subdomains and on contact interfaces. By setting up suitable solution algorithms, the computational efficiency can be improved considerably. The general tendency of the computational efficiency is illustrated with some numerical experiments.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2127-2137
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• 2017

A virtual power plant (VPP) is a system that virtually integrates power resources based on the VPP participating customer (VPC) unit and operates as a power plant. When VPP operators manage resources to maximize their benefits, load reduction instructions may focus on more responsive VPCs, or those producing high profitability, by using VPC resources with high operation efficiency. VPCs may thus encounter imbalance problems during operation. This imbalance in operation time would bring more participation for some VPCs, causing potential degradation of their resources. Such an operation strategy would be not preferable for VPP operators in managing the relationship with VPCs. This issue impedes both continual VPC participation and economical and reliable VPP operation in the long term. An operation algorithm is therefore proposed that considers the operation time of VPC generators for mandatory reduction of power resource consumption. The algorithm is based on constraints of daily and annual operation times when VPP operators of local generators perform capacity-market power transactions. The algorithm maximizes the operator benefit through VPP operations. The algorithm implements a penalty parameter for imbalances in operation times spent by VPC generators in fulfilling their obligations. An evaluation was conducted on VPP operational effects by applying the algorithm to the Korean power market.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.5
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• pp.591-595
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• 2013

This paper presents a method of generation rescheduling using Newton's Approach which searches the solution of the Lagrangian function. The generation fuel cost and $CO_2$ emission cost functions are used as objective function to reallocate power generation while satisfying several equality and inequality constraints. The Pareto optimum in the fuel cost and emission objectives has a number of non-dominated solutions. The economic effects are analyzed under several different conditions, and $CO_2$ emission reductions offered by the use of storage are considered. The proposed approach can explore more efficient and noninferior solutions of a Multiobjective optimization problem. The method proposed is applied to a 4-machine 6-buses system to demonstrate its effectiveness.