Abstract
A new approach for protection of transmission line including TCSC is presented in this paper. The proposed method includes application of Fuzzy Neural Network for distance relaying of a transmission line operating with a thyristor controlled series capacitor (TCSC) protected by MOVs. Here the fuzzy neural network (FNN) is used for calculating fault location on the TCSC line. The FNN structure is seen as a neural network for training and the fuzzy viewpoint is utilized to gain insight into the system and to simplify the model. The number of rules is determined by the data itself and therefore, a smaller number of rules are produced. The network parameters are updated by Extended Kalman Filter (EKF) algorithm. with a pruning strategy to eliminate the redundant rules and fuzzification neurons resulting in a compact network structure . The input to the FNN are fundamental currents and voltages at the relay end, sequence components of current, system frequency and the firing angle with different operating conditions and the corresponding output is the location of the fault from the relaying point The location tasks of the relay are accomplished using different FNNs for different types of fault (L-G,LL-G,LL, LLL).
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Samantaray, S.R., Dash, P.K., Panda, G., Panigrahi, B.K. (2005). Distance Protection of Compensated Transmission Line Using Computational Intelligence. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_24
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DOI: https://doi.org/10.1007/11596448_24
Publisher Name: Springer, Berlin, Heidelberg
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