This study proposes a fuzzy system for tracking the
maximum power point of a PV system for solar panel. The solar panel and maximum
power point tracker have been modeled using MATLAB/Simulink. A simulation model
consists of PV panel, boost converter, and maximum power point tack MPPT
algorithm is developed. Three different conditions are simulated: 1) Uniform
irradiation; 2) Sudden changing; 3) Partial shading. Results showed that fuzzy
controller successfully find MPP for all different weather conditions studied.
FLC has excellent ability to track MPP in less than 0.01 second when PV is subjected
to sudden changes and partial shading in irradiation.
KEYWORDS:
1.
Fuzzy Logic
Controller
2.
Maximum Power
Point
3.
Photovoltaic
System
4.
Partial
Shading
SOFTWARE: MATLAB/SIMULINK
Figure 1. Schematic diagram of PV system with MPPT.
Figure 2. P-V characteristics at different irradiations.
Figure 3. P-V characteristics when partial shading from 1000 to 600 Watt/m2.
Figure 4. Output of fuzzy at1000 Watt/m2.
Figure 5. Output of fuzzy controller. (a) Full shading from 600 to
300 Watt/m2; (b) Full shading from 700 to 400
Watt/m2; (c) Full shading from 900 to 400
Watt/m2; (d) Increasing shading from 300 to 800 Watt/m2.
Figure 6. Comparison between fuzzy and P & O
partial shading (partial shading 1000 to 800 Watt/m2).
CONCLUSION:
In
this study, FLC has been developed to track the maximum power point of PV
system. PV panel, boost converter with FLC connected to a resistive load has
been simulated using Matlab/Simulink. Simulation results have been compared to
nominal power values. The proposed system showed its ability to reach MMP under
uniform irradiation, sudden changes of irradiation, and partial shading.
Simulation results have shown that using FLC has great advantages over
conventional methods. It is found that Fuzzy controller always finds the global
MPP. It is found that fuzzy logic systems are easily implemented with minimal
oscillations with fast convergence around the desired MP
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