Open AccessCOMPARATIVE STUDY OF MPPT BASED ON ARTIFICIAL INTELLIGENCE
Author(s) -
Rajonirina Solofanja Jeannie,
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Razafimahenina Jean Marie,
Andrianaharison Yvon,
Randriamasinoro Njakarison Menja,
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AUTHOR_ID,
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Publication year - 2021
Publication title -
international journal of advanced research
Language(s) - English
Resource type - Journals
ISSN - 2320-5407
DOI - 10.21474/ijar01/13784
Subject(s) - maximum power point tracking , adaptive neuro fuzzy inference system , computer science , maximum power principle , control theory (sociology) , photovoltaic system , fuzzy logic , generator (circuit theory) , neuro fuzzy , power (physics) , artificial intelligence , control engineering , fuzzy control system , engineering , control (management) , inverter , physics , quantum mechanics , electrical engineering
An MPPT or Maximum power point tracking command, associated with an intermediate adaptation stage, allows a photovoltaic generator (GPV) to operate in such a way as to continuously produce the maximum of its power. We present in this paper a new intelligent approach of a MPPT based on the hybrid and adaptive neuro-fuzzy network of ANFIS model. The latter is applied to a SEPIC* converter in order to extract at any time the maximum power available at the generator terminals and transfer it into the load, regardless of the sunshine variation as well as the temperature. The proposed method for a fixed and simple structure implements a Takagi-sugeno fuzzy system. Its performance will be confirmed by the comparison with the fuzzy logic command which is already known with its speed.