Automatic Fault identification in Grid Connected Photovoltaic System using Neural Network Controller

R. Sureshkumar, S. U. Prabha, M. Senthil Arumugam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A significant reason for performance loss is fault occurring in the Photovoltaic (PV) system. Nowadays, with the availability of intelligent control techniques the faults can be identified easily. To identify the fault, Artificial Neural network controller is designed. The power injected to the grid by the photovoltaic system is decreased due to the faults occurring in the system. Usually the fault occurs in Photovoltaic panel, Maximum Power Point Tracking controller (MPPT), Boost converter, inverter and grid. The simulation is carried out on 50 kW PV system by means of Matlab to identify the fault.

Original languageEnglish
Title of host publication2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)
PublisherIEEE
Pages78-80
Number of pages3
ISBN (Electronic)9781728137780
DOIs
Publication statusPublished - 20 Feb 2020
Event2019 International Conference on Computational Intelligence and Knowledge Economy - Dubai, United Arab Emirates
Duration: 11 Dec 201912 Dec 2019

Conference

Conference2019 International Conference on Computational Intelligence and Knowledge Economy
Abbreviated titleICCIKE 2019
Country/TerritoryUnited Arab Emirates
CityDubai
Period11/12/1912/12/19

Keywords

  • Fault Detection
  • Grid Connected PV System
  • Multi Layer Neural Network
  • Neural Network

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

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