• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.79-86
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• 1998

The nonlinear analytic function expansion nodal (AFEN) method is applied to the solution of the time-dependent neutron diffusion equation. Since the AFEN method requires both the particular solution and the homogeneous solution to the transient fixed source problem, the derivation solution method is focused on finding the particular solution efficiently. To avoid complicated particular solutions, the source distribution is approximated by quadratic polynomials and the transient source is constructed such that the error due to the quadratic approximation is minimized. In addition, this paper presents a new two-node solution scheme that is derived by imposing the constraint of current continuity at the interface corner points. The method is verified through a series of applications to the NEACRP PWR rod ejection benchmark problem.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.256-259
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• 1990

In this paper, the selection method of MOI was modified and was applied to KEPCO power system. The results are better than that obtained from the previous method and compare well with those obtained by time simulation.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.20-28
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• 2016

This paper presents a generation rescheduling method for the enhancement of transient stability in power systems. The priority and the candidate generators for rescheduling are calculated by using the energy margin sensitivity. The generation rescheduling formulates the Lagrangian function with the fuel cost and emission such as NO_x and SO_x from power plants. The generation rescheduling searches for the solution that minimizes the Lagrangian function by using the Newton’s approach. While the Pareto optimum in the fuel cost and emission minimization has a drawback of finding a number of non-dominated solutions, the proposed approach can explore the non-inferior solutions of the multiobjective optimization problem more efficiently. The method proposed is applied to a 4-machine 6-bus system to demonstrate its effectiveness.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1239-1241
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• 1999

In this paper, we propose real time transient stability assessment and energy margin estimation using fuzzy approximate reasoning. The proposed method used rotor angle, kinetic energy and acceleration power of generators at clearing time as fuzzy input. In order to calculate energy margin in transient energy function (TEF), we obtained controlling unstable equilibrium point (UEP) using mode of disturbance procedure (MOD). The proposed algorithm is tested on 4-machine, 6-bus, 7-line power system to prove of effectiveness.

• KIEE International Transactions on Power Engineering
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• v.4A no.3
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• pp.134-140
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• 2004

This paper presents an improved group of energy functions reflecting generator damping effects for multi-machine power systems by using Center of Inertia (COI) formulation as an extension of the previous work. Since rotor angles at the Stable Equilibrium Point (SEP) of post-fault systems are generally calculated in COI, system transient energy can be found without assumption of infinite or slack bus, which is a crucial drawback of the absolute rotor angle frame approach. The developed energy functions have a structure preserving property with which it is very flexible to incorporate various models of power system components, especially various load and generator models. The proposed damping-reflected energy functions are applied to the Potential Energy Boundary Surface (PEBS) method, one of the direct methods. Numerical simulation of WSCC 9-bus shows that conservativeness of the PEBS method can be considerably reduced.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.10
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• pp.454-463
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• 2001

This paper presents a method for real-time estimation of TCSC reference quantity in order to enhance the power system transient stability energy margin using artificial neural network in multi-machine system. This paper has the three parts, the first part is to determine the lines to be installed by TCSC. The seconds is to estimate the energy margin using by ANN. To get the critical energy for training, we use the potential energy boundary surface(PEBS) method which is one of the transient energy function(TEF) method. And the last is to determine the TCSC reference quantity. In order to make training data for ANN in this step, we use genetic algorithm(GA). The proposed method is applied to 39-bus, 46-line. 10-machine model system to show its effectiveness.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1175-1182
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• 1999

This paper shows that a well-defined energy function can be developed to reflect the transfer conductances for multi-machine power systems under an assumption that all transmission lines have uniform R/X rations. The energy function is derived by introducing a pure reactive equivalent system for the given system. In this study, a static energy function reflecting transfer conductances is also derived as well as the transient energy function. The proposed static energy function is applied to voltage stability analysis and tested for various sample systems. The test results show that the accuracy of voltage stability analysis can be considerable improved by reflecting transfer conductances into the energy function.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.437-443
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• 2009

In recent years, electric power systems have been experiencing a rapid change due to the increasing electricity market. For the effective use of power system under the deregulated environment, it is important to make a fast and accurate calculation of the maximum available transfer capability (ATC) from a supply point to a demand point. In this paper, the purpose of this research is to calculate ATC fast and accurately for securing the stability of system and raising the efficiency as a result of anticipating transmission congestion according to transmission open access progressed in the future under the regulated environment of electricity market. In this paper, a study utilized a relation of the potential energy and energy function by which calculated CCT and then utilized a relation of PEBS for transient stability ATC calculation. In this paper, ATC was calculated as RPF and Energy Function method and calculation results of each method was compared. Contingence ranking method decided the weak bus by the Eigenvalues of Jacobian matrix and overloading branches by PI-index. As a result, a study proved the fast and accurate ATC calculation method considering transient stability suggested in this paper. Through the case study using New England 39 bus system, it is confirmed that the proposed method can be used for real time operation and the planning of electric market.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.2
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• pp.94-100
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• 2008

Available transfer capability(ATC) quantifies the viable increase in real power transfer from one point to another in a power system. ATC calculation has predominantly focussed on steady-state viability. But ATC assessment with transient stability constraints has a dominant part in overall ATC calculation. ATC assessment requires a reputation of (n-1) security assessment with constraints of thermal limits, voltage stability and dynamic stability. An estimation of determinant contingency screening method is used for computing eigenvalue of Jacobian matrix. This paper proposed a methods to ATC calculation using energy function. Constraints is used thermal limits, voltage stability and transient stability.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.242-244
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• 2000

This paper presents a method for real-time estimation of TCSC quantity in order to enhance the power system transient stability energy margin using fuzzy neural network in multi-machine system. This paper has two parts, the first part is to estimate the energy margin. To set critical energy, we use the potential energy boundary surface(PEBS) method which one of the transient energy function(TEF) method. And the second is to determine the TCSC quantify and the line to be injected. In order to make training data in this step, we use genetic algorithm. The proposed method is applied to 6-bus, 7-line, 4-machine model system to show its effectiveness.