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Alternative fault detection method in electrical power systems based on ARMA model

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

One of the main elements of electrical power systems is the transmission stage; which is exposed to the occurrence of failures and disturbances; and in case of their presence, it puts the stability, reliability and operation of the system at risk; It can cause damage to equipment in case there is any problem with the performance of the protections. In the present investigation an alternative method is proposed for the detection of faults in the transmission systems based on the analysis of the voltage and current phasors by means of the selfregressive moving average model (ARMA), seeking to improve the safety and reliability of transmission power system. For which an optimal deployment of PMU is necessary that considers contingency restrictions in the power system, so that an estimation of system status can be obtained. To test the proposed method, the IEEE 14-Buses test system was used under different case studies.

Original languageEnglish
Title of host publication2019 FISE-IEEE/CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728142302
DOIs
StatePublished - Dec 2019
Event2019 FISE-IEEE/CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019 - Medellin, Colombia
Duration: 4 Dec 20196 Dec 2019

Publication series

Name2019 FISE-IEEE/CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019

Conference

Conference2019 FISE-IEEE/CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019
Country/TerritoryColombia
CityMedellin
Period4/12/196/12/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • ARMA Model
  • Contingencies
  • Fault Detection
  • PMU
  • State Estimation
  • Transmission Lines

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