• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1148-1153
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• 2004

This paper presents the mechanism to increase lateral stability of a mobile robot using an energy stability margin theory. Previous measure of stability used in a wheeled mobile robot has been based on a static stability margin. However, the static stability margin is independent of the height of the robot and does not provide sufficient measure for the amount of stability when the terrain is not a horizontal plane. In this work, the energy stability margin theory, which is dependent on robot's height is used to develop a 2 dof mechanism to increase lateral stability. This proposed mechanism shifts the center of gravity of the robot to the point where the energy stability margin is maximized and overall stability of the robot equipped with this mechanism will be increased.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.7
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• pp.319-326
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• 2006

This paper proposes a novel fault-tolerant gait for Quadruped robots using energy stability margins. The previously developed fault-tolerant gaits for quadruped robots have a drawback of having marginal stability margin, which may lead to tumbling. In the process of tumbling, the potential energy of the center of gravity goes through a maximum. The larger the difference between the potential energy of the center of gravity of the initial position and that of this maximum, the less the robot tumbles. Hence this difference of potential energy, dubbed as Energy Stability Margin (ESM), can be regarded as the stability margin. In this paper, a novel fault-tolerant gait is presented which gives positive ESM to a quadruped robot suffering from a locked joint failure. Positive ESM is obtained by adjusting foot positions between leg swing sequences. The advantage of the proposed fault-tolerant gait is demonstrated in a case study where a quadruped robot with a failed leg walks on a even slope.

• 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.60 no.6
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• pp.1086-1090
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• 2011

This paper presents a method to evaluate generation rescheduling priority using transient energy margin sensitivity for power system operation. A change in any of the functional parameters obviously causes a change in the energy margin. Especially the energy margin sensitivity is evaluated for change with respect to generation. For a given contingency, the energy margin is computed and the respective sensitivities are also computed. It is possible to rank the sensitivities and thereby determine the generators which will affect the energy margin most and hence affect the stability (instability) of the system. The sign of the sensitivity indicates the direction of change in generation for a given change in energy margin.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.