Adaptive neuro-fuzzy inference system based maximum power point tracking of a solar PV module

A. Iqbal, Haitham Abu-Rub, Sk M. Ahmed

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

41 Citations (Scopus)

Abstract

This paper presents and analyses the operation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) based maximum power point tracker (MPPT) for solar photovoltaic (SPV) energy generation system. The MPPT works on the principle of adjusting the voltage of the solar PV modules by changing the duty ratio of the boost converter. The duty ratio of boost converter is calculated for given solar irradiance and temperature condition by a closed-loop control scheme. The ANFIS is trained to generate the maximum power corresponding to the given solar irradiance level and temperature. The response of ANFIS based control system is highly precise and offers very fast response. Simulation results are provided to validate the concept.

Original languageEnglish
Title of host publication2010 IEEE International Energy Conference and Exhibition, EnergyCon 2010
Pages51-56
Number of pages6
DOIs
Publication statusPublished - 2010
Event2010 IEEE International Energy Conference and Exhibition, EnergyCon 2010 - Manama, Bahrain
Duration: 18 Dec 201022 Dec 2010

Other

Other2010 IEEE International Energy Conference and Exhibition, EnergyCon 2010
CountryBahrain
CityManama
Period18/12/1022/12/10

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Keywords

  • Adaptive Neuro-Fuzzy Inference System (ANFIS)
  • boost converter
  • Maximum Power Point tracker
  • Solar PV

ASJC Scopus subject areas

  • Energy Engineering and Power Technology

Cite this

Iqbal, A., Abu-Rub, H., & Ahmed, S. M. (2010). Adaptive neuro-fuzzy inference system based maximum power point tracking of a solar PV module. In 2010 IEEE International Energy Conference and Exhibition, EnergyCon 2010 (pp. 51-56). [5771737] https://doi.org/10.1109/ENERGYCON.2010.5771737