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Improved Variable step P&O MPPT in MATLAB

Improved Variable step P&O MPPT in MATLAB

The discussion in this segment elaborates on two MPPT (Maximum Power Point Tracking) algorithms: Variable Step P&O and Global Scanning MPPT. These algorithms are aimed at efficiently tracking the maximum power output from photovoltaic (PV) systems operating under partial shading conditions.

Variable Step P&O Algorithm Overview

The Variable Step P&O algorithm involves various steps. Initially, it measures the voltage and current of the PV panel. Then, it calculates the current instant power compared to the previous instant power. If conditions are met, the duty cycle is altered incrementally or decrementally to achieve the maximum power point from the solar panel.The algorithm utilizes a variable step calculated by considering the absolute difference in power between current and previous instances. This process helps define the current and previous instants, allowing the step to be adjusted accordingly.

Global Scanning MPPT Algorithm Description

The Global Scanning MPPT algorithm is also applied to identify the maximum power point under changing conditions. It operates by finding maximum power points and comparing them to determine the optimal output. If there's a significant power difference, the algorithm restarts to find a new global maximum point, especially in cases of partial shading.

The algorithm undergoes iterations to calculate and compare power outputs, ensuring that the power difference is within an acceptable range. If the difference exceeds a certain threshold, the algorithm re-initiates to discover the new global maximum point.

Implementing the Algorithms in a PV System Model

In the modeled scenario, three panels are connected in series, maintaining an irradiation level and temperature. These PV panels are connected to a load via a boost converter. The Variable Step P&O and Global Scanning MPPT algorithms take inputs such as PV panel voltage and current, along with a restart condition, to ensure maximum power extraction.

The implementation of these algorithms involves variable step calculations, duty cycle adjustments, and comparisons between current and stored maximum power. It operates through iterations, checking for changes in power that might suggest a need to restart the algorithm and find a new global maximum point.

MATLAB Simulation Results

The MATLAB simulation demonstrated the functioning of these algorithms in changing conditions. As the irradiation levels varied, the algorithm responded by adjusting the duty cycle and power extraction to reach the maximum power point. The simulation showcased waveforms for PV voltage, load voltage, PV current, and load current, representing the efficient adaptation of the algorithms to varying environmental conditions.

Conclusion: Efficiency in Adapting to Dynamic Conditions

In summary, the Variable Step P&O and Global Scanning MPPT algorithms showcase their adaptability and efficiency in tracking the maximum power points in PV systems under changing and partial shading conditions. Through iterations and adaptive strategies, these algorithms ensure optimal power output, even when dealing with dynamic environmental factors.The blog post illustrates the functionalities and efficacy of the Variable Step P&O and Global Scanning MPPT algorithms for PV systems operating under partial shading conditions. The content covers their operation, implementation in a model, and demonstrates their adaptability in dynamic environmental scenarios.

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