Protection of a Transmission Line with Series Compensation Using Artificial Neural Networks

EasyChair Preprint 10260

Abstract

Series compensators regulate and keep acceptable voltage levels in power transmission lines that will reflect positive power quality indexes. However, depending on the kind of compensator to be used, it can add complex parameters to the line modelling due to its non-linear operation and, consequently, in the responses of the current methods utilized for fault location in transmission lines. In this context, this work aims to present an efficient way to determine which section of the two terminals compensated transmission line a single phase to ground fault occurred. The methodology used consists of obtaining voltage and current signals of transmission line terminals. Considering the signs, applying the Discrete S Transform for a pre-processing and, by the calculated coefficients, feeding an Artificial Neural Network so that the determination of in what section the fault occurred, in the left or the right side of the compensator. The obtained results were promising and presented the potentiality of the utilized methodology.

Keyphrases: Classificação de Faltas, Linhas de Transmissão, Redes Neurais Artificiais, TCSC, Transformada Discreta S

@booklet{EasyChair:10260,
  author    = {Matheus do Val Oliveira and Leonardo da Silva Lessa and Mário Oleskovicz},
  title     = {Protection of a Transmission Line with Series Compensation Using Artificial Neural Networks},
  howpublished = {EasyChair Preprint 10260},
  year      = {EasyChair, 2023}}