• Journal of Electrical Engineering and Technology
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• 제8권2호
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• pp.197-205
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• 2013

Real time transient stability assessment mainly depends on real-time prediction. Unfortunately, conventional techniques based on offline analysis are too slow and unreliable in complex power systems. Hence, fast and reliable stability prediction methods and simple stability criterions must be developed for real time purposes. In this paper, two new methods for real time determining critical clearing time based on clustering identification are proposed. This article is covering three main sections: (i) clustering generators and recognizing critical group; (ii) replacing the multi-machine system by a two-machine dynamic equivalent and eventually, to a one-machine-infinite-bus system; (iii) presenting a new method to predict post-fault trajectory and two simple algorithms for calculating critical clearing time, respectively established upon two different transient stability criterions. The performance is expected to figure out critical clearing time within 100ms-150ms and with an acceptable accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.736-740
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• 2004

In order to overcome the problems of simulation methods, the power system transient stability assessment method using critical fault clearing time functions has been developed. Using the above method, this paper has developed the new method which can assess accurately and efficiently the effects of control and protection systems on transient stability which is the most important characteristic to assess in power systems. At first, critical fault clearing time functions CCT(W:load) are defined by taking notice of the fact that transient stability is mainly controlled by fault clearing time and load. Next, the method to be enable to assess accurately and efficiently the effects of control and protection systems on transient stability has been newly developed by using the above functions. Finally, it has been applied to the effect assessment in the occurrence of a three-phase fault in a model power system. Results of application have been clarified its effectiveness.

• KIEE International Transactions on Power Engineering
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• 제2A권4호
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• pp.131-135
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• 2002

This paper describes a new ultra-fast contingency screening algorithm for on-line TSA without time simulation. All machines are represented in a classical model and the stability index is defined as the ratio between acceleration power during a fault and deceleration power after clearing the fault. Critical clustering of machines is done based on the stability index, and the power-angle curve of the critical machines is drawn assuming that the angles of the critical machines increase uniformly, while those of the non-critical ones remain constant. Finally, the critical clearing time (CCT) is computed using the power-angle curve. The proposed algorithm is tested on the KEPCO system comprised of 900-bus and 230-machines. The CCT values computed with the screening algorithm are in good agreement with those computed using the detailed model and the SIME method. The computation time for screening about 270 contingencies is 17 seconds with 1.2 GHz PC.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 추계학술대회 논문집 전력기술부문
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• pp.73-76
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• 2001

This paper presents a new systematic contingency selection, screening and ranking method for on-line transient security assessment. Transient stability of a particular generator is influenced most by fault near it. Fault at the transmission lines adjacent to the generators are selected as contingency. Two screening methods are developed using the sensitivity of modal synchronizing torque coefficient and computing an approximate critical clearing time(CCT) without time simulation. The first method, which considers only synchronizing power, may mislead in some cases since it does not consider the acceleration power. The approximate CCT method, which consider both the acceleration and deceleration power, worked well. Finally the Single Machine Equivalent(SIME) method is implemented using IPLAN of PSS/E for detailed stability analysis.

• 한국태양에너지학회 논문집
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• 제23권3호
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• pp.29-35
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• 2003

Generator for wind power can be either synchronous or asynchronous (induction) types. Induction and synchronous generators behave in a different way when subjected to severe faults. Induction generators does not have an angle stability limit and short circuit in the neighborhood of an Induction generator causes the demagnetization of the machine when the fault is cleared, the voltage raises slowly, while the grid contributes with reactive power to the generator and the magnetic flux recovers. On the other hand in the synchronous generators the recovery of the voltage is immediate, since the excitation of the rotor angle comes from an independent circuit. This paper shows the result of the transient state analysis in the network connected to wind generation system Several case studies have been conducted to determine the effect of the clearing time of a fault on the network stability. It has been found that the critical clearing time can be as low as 61ms in the case of induction generator compared to 370ms in the case of synchronous generator.

• 대한전기학회논문지:전력기술부문A
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• 제49권6호
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• pp.253-258
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• 2000

This paper presents an application of Kohonen neural networks to assess the dynamic security of power systems. The dynamic security assessment(DSA) is an important factor in power system operation, but conventional techniques have not achieved the desired speed and accuracy. The critical clearing time(CCT) is an attribute which provides significant information about the quality of the post-fault system behaviour. The function of Kohonen networks is a mapping of the pre-fault system conditions into the neurons based on the CCTs. The power flow on each line is used as the input data, and an activated output neuron has information of the CCT of each contingency. The trajectory of the activated neurons during load changes can be used in on-line DSA efficiently. The applicability of the proposed method is demonstrated using a 9-bus example.

• 조명전기설비학회논문지
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• 제20권10호
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• pp.41-46
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• 2006

상업용으로 계통에 연계되어 운전되는 대부분의 풍력발전기는 유도발전기가 주로 사용되고 있으며 동기발전기와 다른 양상을 보이고 있어 계통에서의 사고발생 후 정상상태로 복귀할 수 있는 최대의 시간(임계 제거시간)을 이용하여 과도상태를 해석하고 있다. 본 연구에서는 풍력 발전시스템이 연계된 계통에 대해 임계 제거시간에 미치는 요인을 분석하였으며 계통해석 프로그램인 Digsilent Power Factory를 이용하였다. 임계 제거시간에 미치는 요인으로는 연계되는 계통의 단락용량(단락전류). 풍력발전 용량, 풍력발전기 역률, 풍력 발전시스템과 연계되는 계통사이의 전용선 길이, 부하 용량이나 역률 등이 있으며 이들의 변화에 대한 임계 제거시간의 영향을 분석하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.451-452
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• 2007

In this paper, we simulate power system transient stability using object-oriented programming(OOP). OOP is a more flexible method than procedual programming. There are several advantages in dynamic system simulation using OOP. We also calculate critical fault clearing time using energy functions for detailed models.

• 대한전기학회논문지:전력기술부문A
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• 제48권2호
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• pp.107-114
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• 1999

This paper presents an application of artificial neural networks(ANN) to assess the dynamic security of power systems. The basic role of ANN is to provide assessment of the system's stability based on training samples from off-line analysi. The critical clearing time(CCT) is an attribute which provides significant information about the quality of the post-fault system behaviour. The function of ANN is a mapping of the pre-fault, fault-on, and post-fault system conditions into the CCT's. In previous work, a feed forward neural network is used to learn this mapping by using the generation outputs during the fault as the input data. However, it takes significant calculation time to make the input data through the network reduction at a fault as the input data. However, it takes significant calculation time to make the input data through the network reduction at a fault considered. In order to enhance the speed of security assessment, the bus data and line powers are used as the input data of the ANN in thil paper. Test results show that the proposed neural networks have the reasonable accuracy and can be used in on-line security assenssment efficiently.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.535-536
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• 2006

This paper reports investigation into the factors that influence the transient behavior of the wind power generation system following network fault conditions. It is shown that the critical clearing time(CCT) can be affected by various factors contributed by the host network. Such factors include capacity of wind power, power factor, the length of the interfacing line, etc. This investigation is conducted en a simulated grid-connected wind farm using Digsilent Power Factory.