• 조명전기설비학회논문지
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• 제27권1호
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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.

• 전기학회논문지
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• 제60권6호
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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.

• 한국산학기술학회논문지
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• 제15권7호
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• pp.4494-4499
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• 2014

약한 계통은 단락비가 작고 임피던스가 크므로 과도 안정도 여유도가 매우 낮다. 약한 계통에 사고가 발생하면 보호 시스템은 사고 선로를 개방함으로써 사고를 제거하는데 이것은 시스템의 안정도를 더욱 약하게 만든다. 그러므로 약한 계통의 안정도 여유를 증가시키기 위한 하나의 방법은 시스템에 추가적인 발전기를 연결하는 것이다. 본 논문에서는 약한 계통의 안정도 여유도를 증가시키기 위하여 기존의 동기발전기를 추가하는 경우와 풍력발전기의 를 추가하는 경우의 안정도 여유도를 비교한다. PSSE를 이용한 과도안정도 시뮬레이션 결과 풍력발전기가 충분한 제동력을 제공하고 안정도 여유를 증가시킴을 확인할 수 있었다. 풍력발전기를 추가할 때 안정도 여유도는 CCT 기준으로 5배까지 향상되었다.

• Journal of Electrical Engineering and Technology
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• 제3권4호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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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.

• 전기학회논문지
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• 제58권12호
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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.

• 전기학회논문지
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• 제57권7호
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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.

• Journal of Electrical Engineering and Technology
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• 제11권1호
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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.

• 대한전기학회논문지:전력기술부문A
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• 제50권10호
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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.

• 대한전기학회논문지:전력기술부문A
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• 제55권1호
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• pp.1-6
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• 2006

The emergence of competitive power market makes dispatch algorithm with transient stability constraints increasingly important for the transparent power system operation. Heuristic and off-line evaluation for the operation point can produce a discrimination among market players in the deregulated power system. In this paper, a dispatch algorithm with transient stability constraints is proposed. Energy margin under the TEF(Transient Energy Function) structure is adopted as a measure for the stability index. Implementation issues and simulation results are discussed in the context of a 10-bus system