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

    Producción científica: Capítulo del libro/informe/acta de congresoPonencia publicada en las memorias del evento con ISBNrevisión exhaustiva

    3 Citas (Scopus)

    Resumen

    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.

    Idioma originalInglés
    Título de la publicación alojada2019 FISE-IEEE/CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019
    EditorialInstitute of Electrical and Electronics Engineers Inc.
    ISBN (versión digital)9781728142302
    DOI
    EstadoPublicada - dic. 2019
    Evento2019 FISE-IEEE/CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019 - Medellin, Colombia
    Duración: 4 dic. 20196 dic. 2019

    Serie de la publicación

    Nombre2019 FISE-IEEE/CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019

    Conferencia

    Conferencia2019 FISE-IEEE/CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019
    País/TerritorioColombia
    CiudadMedellin
    Período4/12/196/12/19

    Nota bibliográfica

    Publisher Copyright:
    © 2019 IEEE.

    Huella

    Profundice en los temas de investigación de 'Alternative fault detection method in electrical power systems based on ARMA model'. En conjunto forman una huella única.

    Citar esto