Sustainable off-grid power solutions are often based on hybrid energy systems that integrate various renewable sources. Optimizing the size of these installations is crucial to maximizing efficiency, reliability and cost-effectiveness. This research compares two approaches to finding the ideal configuration of a hybrid system using wind turbines, solar panels and an energy storage system. The study uses Particle Swarm Optimization (PSO), an intelligent problem-solving technique, to reduce overall system costs while meeting energy requirements. HOMER Pro software is also used to verify and compare these optimized configurations and model system performance. This provides valuable information on energy balance, reliability and long-term economic viability. Our study focuses on comparing the simulation power of HOMER Pro and the research efficiency of Particle Swarm Optimization (PSO) to analyze hybrid energy systems. While we have obtained optimization results using HOMER Pro, the PSO-based optimization is still ongoing. The use of HOMER Pro for hybrid energy system optimization demonstrates good performance and cost reduction based on NPC and LCOE criteria. Once the PSO optimization results are available, a comparison will be made to evaluate the relative performance of both approaches. This research addresses current challenges in hybrid energy system design and paves the way for future innovations in sustainable power generation.