Title :
Performance analysis of neural network and fuzzy logic based MPPT techniques for solar PV systems
Author :
Gupta, Ankit ; Kumar, Pawan ; Pachauri, Rupendra Kumar ; Chauhan, Yogesh K.
Author_Institution :
Sch. of Eng., Electr. Eng. Dept., Gautam Buddha Univ., Noida, India
Abstract :
The maximum power point tracking (MPPT) technique in the photovoltaic (PV) system is used to achieve maximum power through the solar PV system. Therefore, the interest is generated to design a more effective and efficient MPPT to achieve maximum power transfer to the load. In this context, two MPPT techniques, i.e. artificial neural network (ANN) and fuzzy logic control (FLC) are implemented and their performance is analysed. Both the MPPT techniques are investigated in terms of efficiency and response and they are developed in MATLAB/Simulink environment. Their performance is investigated under variable irradiation conditions and found satisfactory for both the techniques.
Keywords :
fuzzy control; fuzzy logic; maximum power point trackers; neural nets; photovoltaic power systems; power system control; solar power stations; ANN; FLC; MATLAB/Simulink environment; artificial neural network; fuzzy logic based MPPT techniques; fuzzy logic control; maximum power point tracking technique; maximum power transfer; photovoltaic system; solar PV systems; Arrays; Artificial neural networks; Fuzzy logic; Maximum power point trackers; Radiation effects; Training; Voltage control; DC/DC Boost converter; Fuzzy logic; Maximum power point tracking (MPPT); Neural network; Photovoltaic (PV) system;
Conference_Titel :
Power India International Conference (PIICON), 2014 6th IEEE
Print_ISBN :
978-1-4799-6041-5
DOI :
10.1109/34084POWERI.2014.7117722
