Comparative Analysis of Solar and Wind Hybrid System Using Multiple Optimization Algorithms

Power generation in the current scenario is majorly constituted by thermal power plants which use fossil fuels like coal, natural gas. Usage of fossil fuels increases the carbon footprint which causes adverse effects on the environment. The only solution to avoid these issues is through alternate green power resources. In this paper hybrid solar and wind power generation systems have been introduced to get stable power generation without any emission of greenhouse gases. The proposed work aims to develop Solar and Wind Hybrid Power generation in Simulink. This proposed model has been controlled using various optimization methods such as Perturb and Observer, Honeybee Optimization and Firefly Optimization. The issues related to implementing Optimization algorithms in hybrid solar-wind system and the complexities of the control strategies have been discussed. Finally, the proposed simulation results are compared and analyses its performance. Based on the comparative analyses the Firefly Optimization is the most efficient optimization technique for the hybrid Solar and Wind power generation system for EV charging applications.