Application of Artificial Intelligence Techniques for Classification and Location of Faults on Thyristor-Controlled Series-Compensated Line

Dash, PK and Pradhan, AK and Panda, G (2003) Application of Artificial Intelligence Techniques for Classification and Location of Faults on Thyristor-Controlled Series-Compensated Line. Electric Power Components and Systems, 31 (3). pp. 241-260. ISSN 1532-5008

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Official URL: http://dx.doi.org/10.1080/15325000390112170

Abstract

Radial basis function neural networks (RBFNN) and fuzzy neural networks (FNN) are finding increasing attention as AI techniques. Power systems protection is a complex task in which AI techniques are successfully employed. Minimal RBFNN (MRBFNN) is a newer version of neural network that provides a minimum number of neurons using the sequential learning and pruning strategy. On the other hand, the fuzzy neural network, using a pruning strategy, yields fewer fuzzy rules. These new techniques are employed for the Protection of a power network having a thyristor-controlled series capacitor (TCSC) which introduces further complexity into the protection problem. A comparison of the two new schemes is also outlined.

Item Type: Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 23 Aug 2011 07:19
Last Modified: 23 Aug 2011 07:19
URI: http://shdl.mmu.edu.my/id/eprint/2581

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