Particle Swarm Optimization of Hybrid Renewable Energy Systems

Abstract

Hybrid renewable energy systems (HRES) have gained attention due to their potential to provide a reliable and sustainable source of energy. They involve the integration of two or more renewable energy sources along with energy storage systems to ensure a continuous and stable power supply. Off-grid HRES types include PV-based, PV-wind-based, and hydro-based systems, while on-grid HRES can be interconnected with the grid or used in isolated microgrids. Optimization techniques such as particle swarm optimization (PSO) have been applied to HRES to maximize energy efficiency, reduce emissions, and improve human development indices. Mathematical models have been developed to evaluate the emission savings, degradation, and HDI associated with HRES. The PSO algorithm is used to solve the models and the results are discussed in terms of the trade-offs between energy efficiency, emission savings, and HDI. HRES can play a critical role in achieving a sustainable energy future.