PI: Dr. Ahmed Atiah
CoI: Dr. Mohamed Darahouth

Choosing the optimal configuration and capacity planning for a hybrid PV-hydrogen system is a strategic decision-making process that spans approximately 20 years, during which climate and economic factors play a significant role. For this purpose, this research proposes a multi-objective mixed-integer nonlinear programming (MO-MINLP) optimization model that considers economic, technical, and environmental objectives. Additionally, this research utilizes the concept of conditional value at risk (CVaR) in risk management to optimize the energy density over time. The hybrid system includes decision variables such as tilt angle, spacing between PV panels, number of PV panels, number of hydrogen tanks, number of electrolyzers, number of fuel cells, and quantity of hydrogen stored over time. MO optimization helps study the trade-offs among economic, technical, and environmental objectives. We will provide a real-world case to demonstrate the practicability of the optimization model, which involves a PV-hydrogen system to supply power to the residential area at KFUPM.