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.
- Fuzzy Logic Controller
- Maximum Power Point
- Photovoltaic System
- Partial Shading
Figure 1. Schematic diagram of PV system with MPPT.
EXPECTED SIMULATION RESULTS:
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).
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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