Particle Swarm Optimization Approach for Cost Minimization of Hybrid Renewable Energy Sources

Optimizing Hybrid Renewable Energy Sources (HRES) is needed in many aspects. As the population and needs continuously increase, HRES becomes much more necessary as the current technologies cannot satisfy the entire demand. This paper uses MATLAB programming and Simulink to perform the optimization and uses the Particle Swarm Optimization (PSO) for optimization, which is considered one of the best algorithms. There are many isolated and remote communities and cities in the world that cannot connect physically or low budget to a grid for the power supply. There is a large amount of electricity demand in these areas, which is being delivered by the small as well as isolated diesel generators, which is not easy to operate. These diesel generators require a very high cost to operate due to the short supply of crude fuels in these areas and problems in fuel delivery with the complex maintenance of the diesel generators. HRES, such as solar Photovoltaic (PV) as well as wind generators, proposed a feasible alternative for power generation in off-grid communities. Many HRES system have been deployed worldwide, as well as they serve a large variety of applications.