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

Citation

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

Full text not available from this repository.

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
URII: http://shdl.mmu.edu.my/id/eprint/2581

Downloads

Downloads per month over past year

View ItemEdit (login required)