Solar PV Fed BLDC motor for Air cooler Application
Solar energy plays a pivotal role in the world of sustainable power. Harnessing maximum efficiency from solar panels, especially in varying environmental conditions, is a constant pursuit. This article focuses on a simulation model designed in MATLAB for a solar PV system integrated with a motor, aiming to control both irradiation levels and maximize power extraction through Perturb and Observe (P&O) MPPT (Maximum Power Point Tracking).
The simulated model details a system involving solar PV panels and a motor intended for an air cooler application. The simulation enables manipulation of irradiation levels by altering the radiation parameters. By adjusting the irradiation from 0 to 0.5 and further to 1,000 to 400 watts per square meter and beyond, the impact on power extraction from the PV panels is observed and analyzed.
The simulation involves a comprehensive approach, allowing the study and analysis of PV panel parameters, including power ratings, voltage, current, and the dynamics of the bug boost converter for power extraction. The integration of P&O MPPT algorithm and Particle Swarm Optimization (PSO) algorithm with sliding mode control in MATLAB is also demonstrated, presenting an innovative strategy for maximizing power output under varying irradiation conditions.
The model's outputs are displayed, showcasing the fluctuations in PV panel power, bug boost converter output, stator current, EMF, speed, and torque of the system components under varying irradiation levels. The simulation's capabilities enable users to adjust and observe changes in real-time, offering insights into how different irradiation levels impact power extraction and system performance.
The simulation's flexibility allows for practical experimentation by adjusting both the irradiation levels and fixed degradation, and observing the resultant changes in power extraction and efficiency. Users can evaluate the system's response to varying conditions, offering valuable insights into strategies to optimize solar panel performance under different environmental scenarios.
The ability to manipulate irradiation levels and observe their impact on power extraction and system efficiency is pivotal in enhancing our understanding of solar panel behavior in diverse conditions. This model provides a significant learning and analysis tool, empowering researchers, engineers, and enthusiasts in the field of renewable energy to explore and innovate in optimizing solar energy systems.
The seamless manipulation of irradiation parameters within the simulation and the ability to observe real-time changes in power extraction exemplify the potential of controlled irradiation in maximizing solar panel efficiency.