Fault diagnosis of power distribution feeders with PV system using equivalent-input-disturbance approach

Bo Hu, Jinhua She, Ryuichi Yokoyama

Research output: Contribution to journalArticle

Abstract

This paper describes a fault diagnosis method based on the equivalent-input-disturbance (EID) approach to power distribution feeders connected to a photovoltaic (PV) system. Node faults are treated as a system disturbance and are estimated using an EID estimator. First, a dynamic model that contains both the PV system and a power supply utility for the feeder is built. Second, an EID estimator is constructed to estimate the disturbance to the system on the control input channel. Third, a method for abstracting the amount caused by the PV system in the EID is presented to estimate the effect caused by faults. Simulation results demonstrate the validity and superiority of the method.

Original languageEnglish
Pages (from-to)283-290
Number of pages8
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Volume17
Issue number2
Publication statusPublished - 2013 Mar

Keywords

  • Equivalent input disturbance (EID)
  • Fault diagnosis
  • Grid-connected photovoltaic (PV) system
  • Power system

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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