Accurate fault location in high voltage transmission systems comprising an improved thyristor controlled series capacitor model using wavelet transforms and neural network
Cheong, W. J. and Aggarwal, R. K., 2002. Accurate fault location in high voltage transmission systems comprising an improved thyristor controlled series capacitor model using wavelet transforms and neural network. In: Transmission and Distribution Conference and Exhibition 2002: Asia Pacific. IEEE/PES, 2002-01-01.
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This paper describes the applications of discrete wavelet transforms (DWT) coupled with conventional artificial neural networks (ANN) to the development of a fault location technique under an improved TCSC transmission system model. The fault location scheme is modular based whereby fault type is verified before identifying the fault location using ANN. This method relies on utilising DWT to decompose the busbar voltages and line currents obtained from a single terminal into a series of time-scale representations. A feature model using self-organising maps (SOM) is applied herein to verify the fault location capability of the extracted features. Results of computer experiments with simulated faulted TCSC transmission line are included and they indicate that this approach can be used as an effective tool for accurate fault location in TCSC systems. More importantly, it obviates knowledge of firing angle of the TCSC or any predefined assumptions.
|Item Type||Conference or Workshop Items (Paper)|
|Creators||Cheong, W. J.and Aggarwal, R. K.|
|Uncontrolled Keywords||wavelet transforms,simulated faulted tcsc transmission line,power capacitors,power system faults,neural network,accurate fault location,line currents,power engineering computing,thyristor applications,tcsc transmission system model,self-organising feature maps,self-organising maps,time-scale representations,thyristor controlled series capacitor model,firing angle knowledge,feature model,high voltage transmission systems,busbars,fault location,power transmission lines,busbar voltages,discrete wavelet transforms,computer experiments|
|Departments||Faculty of Engineering & Design > Electronic & Electrical Engineering|
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