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# Hybrid Fuzzy PSO MPPT

Implementing Hybrid Fuzzy PSO MPPT for Solar PV Systems in MATLAB

Hybrid Fuzzy PSO MPPT Overview

The hybrid Fuzzy PSO MPPT model is designed to efficiently extract maximum power from solar PV systems. This model integrates the strengths of both Fuzzy Logic and PSO algorithms to adaptively track the maximum power point (MPP) of a solar PV panel.

Model Components

• Solar PV Array: Generates power based on solar irradiation.

• Boost Converter: Adjusts the output voltage and current from the PV panel.

• Load: Represents the system's power consumption.

• PSO Algorithm: Optimizes MPPT by adjusting the duty cycle of the boost converter.

• Fuzzy Logic Controller: Works in conjunction with PSO to refine MPPT adjustments based on real-time conditions.

MPPT Algorithms

The MPPT algorithms aim to adjust the duty cycle of the boost converter to extract maximum power:

• PSO Algorithm: Searches for the optimal duty cycle by evaluating power changes.

• Fuzzy Logic Controller: Provides additional adjustments based on the fuzzy rules applied to power and voltage changes.

Working of Hybrid Fuzzy PSO MPPT

1. Boost Converter Operation

The boost converter adjusts the voltage and current output from the PV panel to match the load requirements. The duty cycle for the boost converter is dynamically adjusted using the hybrid MPPT approach.

2. Power Measurement and Calculation

The system continuously measures PV voltage and current to calculate power. Changes in power due to varying irradiation levels are monitored, and the duty cycle is adjusted accordingly.

3. Hybrid Algorithm Integration

The hybrid approach switches between PSO and Fuzzy Logic based on the rate of power change:

• PSO: Handles major adjustments based on observed power changes.

• Fuzzy Logic: Refines adjustments for finer control.

4. PWM Generator

The Pulse Width Modulation (PWM) generator converts the duty cycle into pulses to control the boost converter, ensuring the PV panel operates at or near the MPP.

Simulation Results and Discussion

The model simulates varying irradiation levels every two seconds. Results show:

• PV Voltage: Maintained around 26V across different irradiation levels.

• Load Voltage and Current: Adjust based on the power provided by the PV panel.

• PV Power: Matches theoretical values closely, indicating effective power extraction.

2. Efficiency

The system’s efficiency is calculated to be around 98.41%, reflecting the effectiveness of the hybrid MPPT approach in optimizing energy extraction.

3. Performance Analysis

• Power Levels: The model successfully tracks and adjusts the power output from the PV panel.

• Current Levels: Shows variation with irradiation, maintaining effective tracking of the MPP.

Conclusion

The hybrid Fuzzy PSO MPPT model effectively optimizes power extraction from a solar PV system, combining the strengths of both PSO and Fuzzy Logic algorithms. This approach ensures high efficiency and adaptability in varying environmental conditions.