Published Paper Details:

The integration of renewable energy sources like photovoltaic (PV) solar panels and wind turbines (WT) into the smart grid is highly beneficial due to the inherent advantages of these resources. Solar and wind energy are not only environmentally friendly and sustainable but also widely available and cost-effective. By leveraging the capabilities of the smart grid, which includes advanced communication, control, and automation technologies, the efficiency and reliability of renewable energy systems can be significantly enhanced. This integration supports the transition to a cleaner energy landscape, reduces dependence on fossil fuels, and helps mitigate the impacts of climate change by lowering greenhouse gas emissions. The hybrid system approach, combining both solar and wind energy, further improves energy stability and availability, compensating for the intermittent nature of these renewable sources.This comparative study aims to evaluate the efficiency and effectiveness of these MPPT methods in optimizing the power output from the hybrid renewable energy system. Particle Swarm Optimization (PSO) is known for its robustness and fast convergence, potentially offering superior performance in tracking the maximum power point under varying environmental conditions. On the other hand, the P&O method is simpler and more widely used, but it may not perform as well in rapidly changing conditions. By implementing and simulating these techniques in MATLAB/SIMULINK, the study provides insights into their practical applications and performance metrics, guiding the development of more efficient renewable energy systems.