SIMULATION AND COMPARATIVE ANALYSIS OF HYBRID RENEWABLE ENERGY SYSTEM FOR ENHANCED ENERGY EFFICIENCY

Abstract: Solar energy is a fantastic clean power source, but its weather-dependent nature makes it highly unpredictable. To beat this volatility and keep the power flowing, we designed and tested a hybrid Photovoltaic-Fuel Cell (PV–FC) system in MATLAB/Simulink. A key part of the puzzle was finding the best way to lock onto maximum solar power, so we put three popular Maximum Power Point Tracking (MPPT) techniques to the test under identical conditions: Perturb and Observe (P&O), Incremental Conductance (INC), and Particle Swarm Optimization (PSO). Our simulations show that the intelligent PSO algorithm is the clear winner, reaching an impressive 97.65% tracking efficiency compared to 94.02% for INC and 90.96% for P&O. It responds much faster to environmental shifts, and when the sun dips, the integrated fuel cell seamlessly steps in to smooth out the supply. Ultimately, this hybrid setup proves to be a highly reliable blueprint for standalone grids, rural electrification, and a more resilient green energy infrastructure.

Keywords: Photovoltaic System, Fuel Cell, MPPT, Particle Swarm Optimization, Hybrid Energy System, MATLAB/Simulink.