ANFIS-based maximum power point tracking control of PV modules with DC-DC converters

Yuan Ting Chu, Li Qiang Yuan, Hsin Han Chiang

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

4 Citations (Scopus)

Abstract

This paper proposes an adaptive neural-fuzzy inference system (ANFIS) based maximum power point tracking (MPPT) system for a photovoltaic (PV) power generating system in standalone operation. To extract the maximum power, the DC-DC buck/boost converter is connected between the PV module and the load. The proposed ANFIS-based MPPT controller performs the fast dynamic response with high accuracy. With the test under varying load conditions, experimental results are provided to validate our approach.

Original languageEnglish
Title of host publication2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages692-697
Number of pages6
ISBN (Electronic)9781479988044
DOIs
Publication statusPublished - 2016 Jan 18
Externally publishedYes
Event18th International Conference on Electrical Machines and Systems, ICEMS 2015 - Pattaya City, Thailand
Duration: 2015 Oct 252015 Oct 28

Publication series

Name2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015

Conference

Conference18th International Conference on Electrical Machines and Systems, ICEMS 2015
Country/TerritoryThailand
CityPattaya City
Period2015/10/252015/10/28

Keywords

  • artificial intelligence
  • maximum power point tracking (MPPT)
  • neural fuzzy systems
  • Photovoltaic (PV) systems
  • solar power generation

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanical Engineering

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