Implementation and Evaluation of Maximum Power Point Tracking (MPPT) Based on Adaptive Neuro-Fuzzy Inference System for Photovoltaic PV System

Yıl 2017, Cilt: 7 Sayı: 3, 1453 - 1474, 27.07.2017

Abd El Hakim Ali Elagori M. Emin Tacer

https://izlik.org/JA43LP56RX

Öz

The
conversion of energy of sunlight into electricity is done using photovoltaic
(PV) cells. This paper introduces, comparing,
analyzing and evaluating the performance of the PV systems which are operating
with MPPTs that work by adaptive neuro fuzzy interference system (ANFIS)
technique with other MPPT algorithms such as Perturb and Observe (P&O)
algorithm, Fuzzy Logic Control (FLC) algorithm and Artificial Neural Network
(ANN) algorithm. These algorithms work to control the duty cycle (D) of the
pulse signal that goes to the switch of the DC-DC converter for maximizing the
power generated by the solar panel. The paper also introduces simulating and
modeling a general PV panel with some adjustable parameters for modelling any real
PV model using its electrical data sheet. In addition, the work tests the model
for the influence of changing in operation solar irradiation and operation
temperature on I-V and P-V curves. MPPT algorithms are implemented using boost
DC-DC converter with constant resistive load. All systems are analyzed and
simulated by using MATLAB-Simulink program. Simulation results show that the ANFIS
and ANN based MPPT method gives faster response to archive the MPP and is more efficient
than FLC MPPT and the P&O MPPT methods.

Anahtar Kelimeler

Photovoltaic cell , maximum power point tracking , fuzzy logic control , artificial neural network , adaptive neuro-fuzzy inference system

Kaynakça

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