MATLAB-Based Fuzzy Logic MPPT for Solar PV System
System Configuration
Solar PV System Setup
The system consists of a solar PV panel connected to a boost converter, which plays a crucial role in adjusting the output voltage to match the load requirements. The selected reference voltage for this implementation is 30V. This specific voltage is crucial for maintaining maximum power output under varying irradiation levels.
Reference Voltage and Irradiation
By fixing the reference voltage at 30V, we aim to optimize power extraction. The algorithm adjusts the output to maintain this voltage, ensuring efficient energy capture from the solar panel across different irradiation scenarios.
Designing the Fuzzy Logic Controller
Creating Membership Functions
The fuzzy logic controller is designed using MATLAB’s fuzzy logic toolbox. Key steps include defining membership functions for two inputs: error and change in error. These inputs help determine the output duty cycle for the boost converter.
Adding Membership Functions: We can create various types of membership functions (triangular, trapezoidal, etc.) to represent our inputs and outputs effectively.
Rule Creation: After defining the membership functions, we establish rules that govern the system's response to changing inputs.
Implementing the Controller
Once the membership functions and rules are set, we load the fuzzy logic design into the MATLAB workspace. This allows us to simulate the system’s performance under different irradiation conditions.
Simulation Results
Power Extraction Analysis
During the simulation, we analyzed power extraction at various irradiation levels, such as 1000W/m², 800W/m², and 400W/m². The results indicated that:
At 1000W/m², the maximum power extracted was approximately 250W.
As irradiation decreased, the system efficiently adjusted the duty cycle to maintain optimal power extraction.
Duty Cycle Adjustments
The algorithm demonstrated a dynamic response to changes in irradiation levels. For instance, as the irradiation decreased from 1000W/m² to 800W/m², the duty cycle adjusted from around 66.4% to maintain maximum power output effectively.
Performance under Variable Loads
Testing with Load Changes
To further evaluate the system, we tested it under variable load conditions while keeping irradiation constant. The fuzzy logic MPPT algorithm proved effective, maintaining maximum power extraction even as load conditions changed.
Initial Load: At the start, the system extracted 250W at 1000W/m².
Load Addition: When additional load was introduced, the power level briefly dipped but quickly stabilized back to maximum levels due to the adaptive nature of the MPPT algorithm.
Conclusion
The MATLAB-based fuzzy logic MPPT for solar PV systems offers an efficient solution for maximizing solar energy extraction. The adaptability to changing irradiation and load conditions showcases its potential for real-world applications in solar energy systems.
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