A multi-objective optimization model based on mixed integer linear programming for sizing a hybrid PV-hydrogen storage system

In this paper, a multi-objective mixed-integer linear programming model is developed to design a hybrid PV-hydrogen renewable energy system considering two objective functions; minimizing total life costs and loss probability of power supply. The decisions of the hybrid system include the number of PV panels, the number of hydrogen tanks, the number of electrolyzers, the number of fuel cells, and quantity of hydrogen stored over time. An exact method embedded in GAMS software is used to solve the developed model. The model is validated using an electrical testing lab in Saudi Arabia with hourly power demand. Different plans are chosen from the obtained optimal Pareto solutions. For example, one of the plans found that a hybrid system with 212 PV panels, 617 hydrogen tanks, 30 electrolyzers, and 21 fuel cells is sufficient to satisfy the electrical testing lab load with an annual cost of $61663, the loss of power supply probability is 10%, and the CO₂ saving of 214,882 kg of CO₂. The results indicated the feasibility of combining an electrolyzer, hydrogen tank storage, and fuel cell with a renewable energy system; however, the cost of energy generated is still high because of the high investment cost. Furthermore, the findings revealed that hydrogen technologies are appealing as an energy storage solution for intermittent renewable energy systems and in other applications such as transportation, residential, and industrial sectors. In addition, the findings demonstrated the possibility of using renewable energy as a source of energy, namely, in Saudi Arabia. However, weather conditions, geomorphological conditions, and climatic dependence on hydrogen fuel cell technology can harm the energy yields produced by renewable energy systems.