• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.567-575
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• 2008

Transient security assessment(TSA) is becoming an essential requirement not only for security monitoring but also for stabilizing control of power systems under new electricity environments. It has already been pointed out that fast transient stability study is an important part for monitoring and controlling system security. In this paper, we discuss an energy function method for stabilizing control of transiently unstable systems by introducing generator tripping system to enhance the transient stability of power systems. The stabilization with less tripped power can be obtained by tripping the generators faster than out-of-synchronism relay. Fast transient stability assessment based on the state estimation and direct transient energy function method is an important part of the stabilizing scheme. It is possible to stabilize the transiently unstable system by tripping less generators before the action of out-of-synchronism relay, especially when a group of generator are going to be out-of-synchronism. Moreover, the amount of generator output needed for tripping can be decided by Transient Energy Function(TEF) method. The main contribution of this paper is on the stabilizing scheme which can be running in the Wide Area Control System.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2311-2315
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• 2009

This paper presents a method to apply energy margin for assesment of total transfer capability (TTC). In order to calculate energy margin, two values of the transient energy function have to be computed. The first value is transient energy that is the sum of kinetic and potential energy at the end of fault. The second is critical energy that is potential energy at controlling UEP(Unstable Equilibrium Point). It is seen that TTC level is determined by not only bus voltage magnitudes and line thermal limits but also transient stability. TTC assessment is compared by the repeated power flow(RPF) method and optimization method.

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.468-475
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• 2008

This paper presents a method for estimating the transient stability status of the power system using radial basis function(RBF) neural network with a fast hybrid training approach. A normalized transient energy margin(${\Delta}V_n$) has been obtained by the potential energy boundary surface(PEBS) method along with a time-domain simulation technique, and is used as an output of the RBF neural network. The RBF neural network is then trained to map the operating conditions of the power system to the ${\Delta}V_n$, which provides a measure of the transient stability of the power system. The proposed approach has been successfully applied to the 10-machine 39-bus New England test system, and the results are given.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.161-166
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• 2011

This paper proposes an algorithm for determining critical generator lists using accelerating power and synchronizing power coefficient (SPC), and critical generator group (CGG) from CGG candidates, which is a combination of critical generators. The accurate determination of CGG provides a more accurate energy margin while providing system operator with information of possible unstable generator group. Classical transient energy function (TEF) method selects the critical generators with big corrected kinetic energy of each generator at the moment of fault removal. However, the generator with small acceleration after fault, that is, the generator with small corrected kinetic energy, is also likely to belong to CGG if the generator has small synchronizing power. The proposed algorithm has been verified to be effective compared with the classical TEF method. We utilized the power system of Korean Electric Power Corporation(KEPCO) as a test system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.1
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• pp.68-75
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• 2013

This paper presents a scheme to improve transient stability using Newton's Approach for generation rescheduling. For a given contingency, the energy margin and sensitivities are computed. The bigger energy margin sensitivity of generator is, the more the generation of the generator effects to the transient stability. According to energy margin sensitivity, the control variables of generation rescheduling are selected. The fuel cost function is used as objective function to reallocate power generation. The results are compared to the results of time simulation to show its the effectiveness.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1123-1128
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• 2008

The necessity of online dynamic security assessment is getting apparent under Electricity Market environments, as operation of power system is exposed to more various operating conditions. For on-line dynamic security assessment, fast transient stability analysis tool is required for contingency selection. The TEF(Transient Energy Function) method is a good candidate for this purpose. The clustering of critical generators is crucial for the precise and fast calculation of energy margin. In this paper, we propose a new method for fast decision of mode of instability by using stability indices and energy margin. The method is a new version of our previous paper.[1] Case studies are showing very promising results.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.153-156
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• 1992

Transient stability analysis of Korea Electric power Corporation(KEPCO) system is conducted by time simulation method, and the method is robust and reliable. But, time simulation consumes enormous computing resources and engineering time, and it does not provide a measure of the degree of stability of the system. Therefore, this method does not apply to every changed condition appropriately and quickly in planning and operating. And Transient Energy Function (TEF) method whis can assess quickly and quantatively the degree of stability of the system and which judges the stability and the instability to analyse transient dynamic charater of the system by mutual changing kinetic energy and potential energy, is developed. TEF method analyses the first Swing transient stability of the system by using the thought that if after disturbance happening, the increase of all the rotator kinetic energy changes into the potential energy after diturbance clearing, the system is stable, otherwise the system is unstable. This paper represents the availabiIity of the TEF method by comparing with time simulation method on the two cases.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.152-154
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• 2001

This paper presents a method for determination of UPFC control quantity in order to enhance the power system transient stability energy margin using Genetic Algorithms in multi-machine system. We use the minimization of energy margin as the object function in GA. To set critical energy, we use the potential energy boundary surface(PEBS) method. PEBS is one of the transient energy function(TEF) method. And we used the series voltage compensator as the UPFC model. The proposed method is applied to 6-bus, 7-line, 4-machine model system to show its effectiveness.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.478-489
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• 2013

The controllability and stability of power systems can be increased by Flexible AC Transmission Devices (FACTs). One of the FACTs devices is Interline Power-Flow Controller (IPFC) by which the voltage stability, dynamic stability and transient stability of power systems can be improved. In the present paper, the convenient operation and control of IPFC for transient stability improvement are considered. Considering that the system's Lyapunov energy function is a relevant tool to study the stability affair. IPFC energy function optimization has been used in order to access the maximum of transient stability margin. In order to control IPFC, a Brain Emotional Learning Based Intelligent Controller (BELBIC) and PI controller have been used. The utilization of the new controller is based on the emotion-processing mechanism in the brain and is essentially an action selection, which is based on sensory inputs and emotional cues. This intelligent control is based on the limbic system of the mammalian brain. Simulation confirms the ability of BELBIC controller compared with conventional PI controller. The designing results have been studied by the simulation of a single-machine system with infinite bus (SMIB) and another standard 9-buses system (Anderson and Fouad, 1977).

• 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.