Improved Variable step P&O MPPT in MATLAB
Introduction
Optimizing power generation from solar panels is essential for maximizing efficiency and harnessing renewable energy effectively. However, factors like partial shading can significantly impact the performance of PV systems, leading to suboptimal power output.
To address this challenge, advanced algorithms like Variable Step MPPT and Global Scanning MBPT offer innovative solutions for dynamically adjusting the operating parameters of PV systems to extract the maximum available power under varying conditions.
Variable Step MPPT Algorithm
The Variable Step MPPT algorithm utilizes real-time measurements of PV panel voltage and current to dynamically adjust the duty cycle of the converter, thereby optimizing power extraction. By comparing current and previous instant power values, the algorithm intelligently adjusts the duty cycle to track the maximum power point (MPP) of the PV system.
Global Scanning MBPT Algorithm
In parallel, the Global Scanning MBPT algorithm continuously scans for the global maximum power point by iteratively adjusting the operating parameters of the PV system. This iterative process involves comparing current power values with previously stored maximum power values and dynamically updating the operating parameters to track the optimal power point.
Implementation and Simulation
Using MATLAB, we implemented and simulated the Variable Step MPPT and Global Scanning MBPT algorithms in a PV system setup. The simulation involved three PV panels connected in series, each subjected to varying irradiation levels.
By simulating the algorithms under different irradiation conditions, we demonstrated their effectiveness in maximizing power extraction from the PV system. The algorithms adaptively adjusted the system's operating parameters to track the optimal power point, even under partial shading conditions.
Conclusion
In conclusion, the Variable Step MPPT and Global Scanning MBPT algorithms offer robust solutions for maximizing power extraction from PV systems, particularly in scenarios with partial shading. By intelligently adjusting the system's operating parameters, these algorithms enable efficient utilization of solar energy resources and contribute to the advancement of renewable energy technologies.