Optimization of the economic-technical model for hydrogen production with an approach to utilizing solar power plants and waste-to-energy conversion

The present research work is related to the optimization of a hybrid renewable energy system, combining Waste-to-Energy (WTE) and Photovoltaic (PV) technologies for hydrogen production by means of water electrolysis in both on-grid and off-grid operation modes. A WTE plant of 3 MW rated capacity is combined with a PV array of capacity varying from 0.5 to 3 MW. The Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Simulated Annealing (SA), Gradient Descent, and Newton's Method algorithms were used to minimize Levelized Cost of Hydrogen (LCOH) while ensuring energy reliability. In the on-grid scenario, the minimum LCOH of around -399.215 $/kg was achieved by PSO, GA, and SA, which indicates cost-effectiveness with the help of grid exportation and importation. Whereas, in the off-grid case, LCOH values are higher: the minimum value of LCOH by PSO, GA, and SA was 34.81 $/kg, while the highest was obtained from Gradient Descent with 42.85 $/kg. The main problems that the configuration faced in an off-grid setting were related to not being able to satisfy energy demand and increased curtailment rates. These findings evidence the economic advantages of on-grid systems and underline the necessity for additional measures in off-grid setups, such as energy storage, to reach higher performance and reliability.