• Journal of Electrical Engineering and Technology
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• v.8 no.2
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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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.585-593
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• 2004

Fault-tolerant gait planning in legged locomotion is to design gaits with which legged robots can maintain static stability and motion continuity against a failure in a leg. For planning a robust and deadlock-free fault-tolerant gait, kinematic constraints caused by a failed leg should be closely examined with respect to remaining mobility of the leg. In this paper, based on the authors's previous results, deadlock avoidance scheme for fault-tolerant gait planning is proposed for a hexapod robot walking over even terrain. The considered fault is a locked joint failure, which prevents a joint of a leg from moving and makes it locked in a known position. It is shown that for guaranteeing the existence of the previously proposed fault-tolerant tripod gait of a hexapod robot, the configuration of the failed leg must be within a range of kinematic constraints. Then, for coping with failure situations where the existence condition is not satisfied, the previous fault-tolerant tripod gait is improved by including the adjustment of the foot trajectory. The foot trajectory adjustment procedure is analytically derived to show that it can help the fault-tolerant gait avoid deadlock resulting from the kinematic constraint and does not make any harmful effect on gait mobility. The post-failure walking problem of a hexapod robot with the normal tripod gait is addressed as a case study to show the effectiveness of the proposed scheme.

• 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.