• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.41-46
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• 2006

Generation of electricity using wind power has received considerable attention worldwide in recent years. In order to investigate the impacts of the integration of wind farm into utilities' network, various studies have been investigated. One such impact is related to the Critical Clearing Time (CCT) of wind power generation system. 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 CCT can be affected by various factors contributed by the network. Such factors include capacity of wind power, power factor, the length of the interfacing line, etc. This investigation is conducted on a simulated grid-connected wind farm using Digsilent Power Factory.

• KIEE International Transactions on Power Engineering
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• v.2A no.4
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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.

• Proceedings of the KIEE Conference
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• 2001.11b
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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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.6
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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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2388-2392
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• 2013

Wind generation systems are very different in nature from conventional generation systems. Therefore it is necessary to research dynamic characteristics of wind generation systems connected to a power system. The stability analysis of wind turbine generator is an important issue in the operation of the power system. The result of angular stability of the power system that consists of only synchronous generators is different from that of the power system including wind turbine generators. This is due to the fact that generators connected to wind turbines are generally induction generators. The angular stability assessing synchronization of generators is determined by its corresponding critical clearing time(CCT). Wind turbine models for the analysis of power system are varied and difficult to use, but now these are standardized into four types. In this paper, the analysis of the CCT of the power system connected to wind farm considering the location and capacity is performed by using DFIG(Doubly-Fed induction Generator) wind turbine built-in type3 model in PSS/E-32.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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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.

• KIEE International Transactions on Power Engineering
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• v.11A no.4
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• pp.15-20
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• 2001

Power system stability is correlated with system structure, disturbances and operating conditions, and power flows on transmission lines are closely related with those conditions. This paper proposes a methodology to identify correlative power flows for power system transient and small-signal stability prediction. In transient stability sense, the Critical Clearing Time is used to select some dominant contingencies, and Transient Stability Prediction index is proposed for the quantitative comparison. For small-signal stability discusses a methodology to identify crucial transmission lines for stability prediction by introducing a sensitivity factor based on eigenvalue sensitivity technique. On-line monitoring of the selected lines enables to predict system stability in real-time. Also, a procedure to make a priority list of monitored transmission lines is proposed. The procedure is applied to a test system, and it shows capabilities of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.5
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• pp.271-278
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• 2003

Power system stability is correlated with system structure, disturbances and operating conditions, and power flows on transmission lines are closely related with those conditions. This paper proposes a methodology to identify correlative power flows for power system transient and small-signal stability prediction. In transient stability sense, the Critical Clearing Time is used to select some dominant contingencies, and Transient Stability Prediction index is proposed for the quantitative comparison. For small-signal stability, this paper discusses a methodology to identify crucial transmission lines for stability Prediction by introducing a sensitivity factor based on eigenvalue sensitivity technique. On-line monitoring of the selected lines enables to predict system stability in real-time. Also, a Procedure to make a priority list of monitored transmission lines is proposed. The procedure is applied to a test system and the KEPCO systems in the year of 2003 and it shows capabilities of the proposed method

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.1897-1904
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• 2008

In this paper, the method for effective stability analysis of Jeju power system in 2011 is proposed. The stability analysis of Jeju power system was carried out by using proposed method In case of Jeju power system with wind turbine generators or without wind turbine generators, including CSC HVDC or VSC HVDC. The steady-state stability is validated by SCR and ESCR, PV curve, QV curve. And the transient stability is analyzed by CCT(Critical Clearing Time). VSC HVDC has more advantages than CSV HVDC on the stability. Also, Jeju power system without wind turbine generators has more advantages than Jeju power system with Wind Turbine Generators on the stability.