MATLAB Implementation of Incremental Conductance MPPT for Solar PV System (PART 2)
Introduction
We explored the workings of the Incremental Conductance Maximum Power Point Tracking (MPPT) algorithm for solar photovoltaic (PV) systems. Today, we’ll dive into the practical aspects of implementing this algorithm using MATLAB. Whether you’re new to solar PV systems or looking to enhance your MATLAB skills, this guide will walk you through the process, including system setup, coding, and performance evaluation.
System Overview
The focus of this implementation is a solar PV system equipped with a 250-watt panel. The system includes:
Solar PV Panel: Rated at 250 watts, with specific values for maximum power voltage and current.
Boost Converter: Used to adjust the voltage and current from the PV panel.
Variable Loads: To test the system’s performance under different load conditions.
Incremental Conductance MPPT Algorithm: The core algorithm for optimizing power output.
PV Panel Specifications
The solar PV panel used in this example features:
Maximum Power: 250 watts.
Maximum Voltage at Power Point: 30.7 volts.
Current at Maximum Power Point: Approximately 8.5 amps.
MATLAB Coding for Incremental Conductance MPPT
The implementation involves several key steps and parameters:
Initial Parameters: Set initial duty cycle to 0.42, with maximum and minimum values of 0.85 and 0.1, respectively. The duty cycle change is 0.00205.
Input Variables: Voltage and current from the PV panel are measured and stored as global variables.
Algorithm Logic:
Change Calculations: Compute changes in voltage and power.
Duty Cycle Adjustment: Adjust the duty cycle based on whether the change in current and voltage is increasing or decreasing.
Condition Checking: The algorithm checks conditions to determine whether to increase or decrease the duty cycle to maintain optimal power tracking.
The MATLAB code navigates through these calculations and adjustments iteratively until the maximum power point is reached.
Simulation and Performance Analysis
We conducted simulations to test the performance of the incremental conductance MPPT algorithm under varying irradiation conditions:
Initial Conditions: Irradiation starts at 1000 watts per meter square with a temperature of 25°C.
Irradiation Variations: The irradiation is reduced stepwise to 800, 600, and finally 400 watts per meter square. The algorithm effectively tracks the maximum power point throughout these changes.
Key Observations:
Tracking Efficiency: The incremental conductance MPPT algorithm successfully tracks the maximum power output even as irradiation levels change.
Simulation Results: The power tracking remained effective with minor fluctuations corresponding to changes in irradiation.
Impact of Load Variations
We also explored how varying the load affects the system:
Load Testing: Loads of 5 ohms, 30 ohms, and 60 ohms were used to assess performance.
Load Change Observations: Despite changes in load, the MPPT algorithm continued to track the maximum power point effectively, demonstrating its robustness in handling different load conditions.
Conclusion
This guide has provided a detailed overview of implementing the Incremental Conductance MPPT algorithm in MATLAB. By following the outlined steps and understanding the key aspects of the algorithm and its performance, you can effectively optimize the power output of your solar PV system.
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